During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h2/(4√2),where h is the piecewise length.展开更多
An efficient and innovative method is presented for the stress-related structural topology optimization(TO)in coupled mechanical-pressure systems by leveraging flexible polygonal meshes.With a polytopal composite fini...An efficient and innovative method is presented for the stress-related structural topology optimization(TO)in coupled mechanical-pressure systems by leveraging flexible polygonal meshes.With a polytopal composite finite element approach,the volumetric locking in nearly incompressible materials is reduced.A fluid-flow-based model is built,in which a design-dependent pressure variable is introduced to capture the loading conditions within the system.The P-norm approach consolidates the stress metrics into a global measure,while the clustered regional scaling and adaptive techniques enhance the solutions for stress-limited cases.The primary contributions of this work include a novel framework for addressing the stress challenges in coupled mechanical-pressure systems via flow-based modeling,the adaptability to both compressible and nearly incompressible materials,and the compatibility with diverse mesh types,including triangular,quadrilateral,and polygonal elements.The numerical examples demonstrate,for the first time,optimized topologies for nearly incompressible materials under stress constraints in coupled mechanical-pressure environments,emphasizing the unique strength of this approach.展开更多
The global incidence of pediatric obesity has increased rapidly over the past few decades.Scientific evidence has repeatedly shown that behavioral and emotional challenges are frequently observed in children with over...The global incidence of pediatric obesity has increased rapidly over the past few decades.Scientific evidence has repeatedly shown that behavioral and emotional challenges are frequently observed in children with overweight or obesity[1-2],as evidenced by a landmark case-control design study revealing that obese children have 7.15 times higher odds of developing mental health disorders in adolescence than their normal-weight peers[1].展开更多
Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integra...Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integrated with topology optimization,achieving significant attention and progress in large-scale problems.This work aims to investigate how much benefit can be obtained by combining parallel computing and machine learning techniques to enhance the efficiency of large-scale topology optimization algorithms.Accordingly,a parallel problem independent machine learning(PIML)-enhanced topology optimization method is proposed.The PIML model substantially reduces the dimension of the condensed stiffness matrix and its computational cost,and parallel computing reduces the workload per process and enables the application of a parallel multigrid solver.Besides,several techniques,such as matrix-free implementation,direct condensation of uniform coarse elements,and adjusting computational resource limits,have been developed to enhance computational efficiency.The weak scaling efficiency,strong scaling speedup,and maximum achievable efficiency of the proposed method are validated across multiple numerical examples,showing significant improvement in the tractable problem size and solution efficiency compared to traditional topology optimization algorithms.展开更多
The proliferation of carrier aircraft and the integration of unmanned aerial vehicles(UAVs)on aircraft carriers present new challenges to the automation of launch and recovery operations.This paper investigates a coll...The proliferation of carrier aircraft and the integration of unmanned aerial vehicles(UAVs)on aircraft carriers present new challenges to the automation of launch and recovery operations.This paper investigates a collaborative scheduling problem inherent to the operational processes of carrier aircraft,where launch and recovery tasks are conducted concurrently on the flight deck.The objective is to minimize the cumulative weighted waiting time in the air for recovering aircraft and the cumulative weighted delay time for launching aircraft.To tackle this challenge,a multiple population self-adaptive differential evolution(MPSADE)algorithm is proposed.This method features a self-adaptive parameter updating mechanism that is contingent upon population diversity,an asynchronous updating scheme,an individual migration operator,and a global crossover mechanism.Additionally,comprehensive experiments are conducted to validate the effectiveness of the proposed model and algorithm.Ultimately,a comparative analysis with existing operation modes confirms the enhanced efficiency of the collaborative operation mode.展开更多
Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta...Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.展开更多
Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN mode...Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN models are limited in their ability to actively suppress noise,which constrains their robustness and precision in solving time-varying problems.This paper introduces a novel active noise rejection ZNN(ANR-ZNN)design that enhances noise suppression by integrating computational error dynamics and harmonic behaviour.Through rigorous theoretical analysis,we demonstrate that the proposed ANR-ZNN maintains robust convergence in computational error performance under environmental noise.As a case study,the ANR-ZNN model is specifically applied to time-varying matrix inversion.Comprehensive computer simulations and robotic experiments further validate the ANR-ZNN's effectiveness,emphasising the proposed design's superiority and potential for solving time-varying problems.展开更多
With the development of technology,diffusion model-based solvers have shown significant promise in solving Combinatorial Optimization(CO)problems,particularly in tackling Non-deterministic Polynomial-time hard(NP-hard...With the development of technology,diffusion model-based solvers have shown significant promise in solving Combinatorial Optimization(CO)problems,particularly in tackling Non-deterministic Polynomial-time hard(NP-hard)problems such as the Traveling Salesman Problem(TSP).However,existing diffusion model-based solvers typically employ a fixed,uniform noise schedule(e.g.,linear or cosine annealing)across all training instances,failing to fully account for the unique characteristics of each problem instance.To address this challenge,we present GraphGuided Diffusion Solvers(GGDS),an enhanced method for improving graph-based diffusion models.GGDS leverages Graph Neural Networks(GNNs)to capture graph structural information embedded in node coordinates and adjacency matrices,dynamically adjusting the noise levels in the diffusion model.This study investigates the TSP by examining two distinct time-step noise generation strategies:cosine annealing and a Neural Network(NN)-based approach.We evaluate their performance across different problem scales,particularly after integrating graph structural information.Experimental results indicate that GGDS outperforms previous methods with average performance improvements of 18.7%,6.3%,and 88.7%on TSP-500,TSP-100,and TSP-50,respectively.Specifically,GGDS demonstrates superior performance on TSP-500 and TSP-50,while its performance on TSP-100 is either comparable to or slightly better than that of previous methods,depending on the chosen noise schedule and decoding strategy.展开更多
Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emoti...Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emotional intelligence,and perceived social support.This study examined how gender,relational trauma,attachment dimensions,resilience,and emotional intelligence contribute to the presence of somatic and eating difficulties in this population.Methods:The sample included 46 adolescents(63%female;ages 12–17,Mean=14.85,Standard Deviation(SD)=1.49)residing in child protection institutions in Uruguay.Participants completed self-report measures assessing childhood relational trauma(CaMir),attachment dimensions(anxiety and avoidance),resilience,emotional intelligence(adaptability and stress management),social support(MOS),and psychosocial adjustment(SENA subscales of somatization and eating problems).Using a fuzzy-set Qualitative Comparative Analysis(fsQCA)approach,distinct configurations of risk and protective factors associated with elevated levels of somatization and eating problems were identified.Results:Relational trauma and attachment anxiety showed moderate associations with both somatization and eating problems(r=0.52–0.57,p<0.01),whereas stress management was negatively associated with both outcomes(r=−0.37 to−0.47,p<0.05).FsQCA revealed multiple configurations of risk and protective factors explaining 81–90%of cases,with solution consistencies ranging from 0.83 to 0.87.Results suggest that relational trauma and attachment anxiety are key risk conditions,whereas resilience,emotional regulation,and perceived social support function as protective factors.Conclusions:Findings highlight the importance of considering multifactorial patterns of vulnerability and protection rather than single predictors and underscore the need for tailored interventions that strengthen resilience and emotional skills while addressing the impact of early relational trauma.展开更多
The newly formulated non-Newtonian rivulet flows streaming down an inclined planar surface,with additional periodic perturbations arising from the application of the 2nd Stokes problem to the investigation of rivulet ...The newly formulated non-Newtonian rivulet flows streaming down an inclined planar surface,with additional periodic perturbations arising from the application of the 2nd Stokes problem to the investigation of rivulet dynamics,are demonstrated in the current research.Hereby,the 2nd Stokes problem assumes that the surface,with a thin shared layer of the fluid on it,oscillates in a harmonic manner along the x-axis of the rivulet flow,which coincides with the main flow direction streaming down the underlying surface.We obtain the exact extension of the rivulet flow family,clarifying the structure of the pressure field,which fully absorbs the arising perturbation.The profile of the velocity field is assumed to be Gaussian-type with a non-zero level of plasticity.Hence,the absolutely non-Newtonian case of the viscoplastic flow solution,which satisfies the motion and continuity equations,is considered(with particular cases of exact solutions for pressure).The perturbed governing equations of motion for rivulet flows then result in the Riccati-type ordinary differential equation(ODE),describing the dynamics of the coordinate x(t).The approximated schematic dynamics are presented in graphical plots.展开更多
In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zer...In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zero-points distribution of the solutions and separate the single valued analytic branch of the solutions with square roots,then convert the problem to a Riemann boundary value problem in variable exponent Lebesgue spaces and discuss the singularity of solutions at individual zeros belonging to curve.We consider two types of cases those where the coefficient is Hölder and those where it is piecewise Hölder.Then we solve the Hilbert boundary value problem with square roots in variable exponent Lebesgue spaces.By discussing the distribution of the odd-order zero-points for solutions and the method of symmetric extension,we convert the Hilbert problem to a Riemann boundary value problem.The equivalence of the transformation is discussed.Finally,we get the solvable conditions and the direct expressions of the solutions in variable exponent Lebesgue spaces.展开更多
Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recov...Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.展开更多
Large language models(LLMs)have demonstrated considerable ability in solving various tasks via Chain-of-Thought(CoT)prompting,which has precipitated extensive research into their application for complex mathematical r...Large language models(LLMs)have demonstrated considerable ability in solving various tasks via Chain-of-Thought(CoT)prompting,which has precipitated extensive research into their application for complex mathematical reasoning problems.However,current research on mathematical reasoning with CoT predominantly focuses on textual mathematical tasks,such as math word problems,while paying limited attention to multimodal geometric scenarios.To bridge this gap,we propose KG-HoT,a model that harnesses the generative and comprehension capabilities of Multimodal large language models(MLLMs)to enhance complex geometric problem-solving in multimodal systems.Our knowledge-grounded approach enables MLLMs to generate hybrid chains-of-thought operating on dual tracks—language-based reasoning and program-based reasoning—which serve as teaching signals for smaller models.Furthermore,we design an instruction tuning framework that trains these dual reasoning tracks collaboratively within a unified architecture,enabling mutual enhancement and efficient knowledge distillation for complex geometric problem solving.Extensive experimental results demonstrate that KG-HoT achieves superior performance compared to existing approaches on multiple geometry problem-solving benchmarks.展开更多
Scientific computing has become a cornerstone of modern scientific discovery and engineering innovation.With the rapid advancement of computational power and numerical algorithms,problems that were once analytically i...Scientific computing has become a cornerstone of modern scientific discovery and engineering innovation.With the rapid advancement of computational power and numerical algorithms,problems that were once analytically intractable can now be studied through accurate simulations and large-scale numerical experiments.Scientific computing provides a bridge between mathematical theory,computational algorithms,and real-world engineering applications,enabling researchers to model complex phenomena such as fluid flow,structural deformation,wave propagation,stochastic processes,and nonlinear dynamical systems.The special issue entitled“Scientific Computing and Its Application to Engineering Problems”was conceived to bring together high-quality research contributions that demonstrate the role of computational mathematics in solving challenging engineering problems.The issue highlights both theoretical advances in numerical methods and their practical deployment in real-world engineering scenarios,with emphasis on robustness,computational efficiency,stability,and scalability.展开更多
We consider the free boundary problem for the Euler-Fourier system that describes the motion of compressible, inviscid and heat-conducting fluids. The effect of surface tension is neglected and there is no heat flux a...We consider the free boundary problem for the Euler-Fourier system that describes the motion of compressible, inviscid and heat-conducting fluids. The effect of surface tension is neglected and there is no heat flux across the free boundary. We prove the local well-posedness of the problem in Lagrangian coordinates under the Taylor sign condition. The solution is produced as the limit of solutions to a sequence of tangentially-smoothed approximate problems, where the so-called corrector is crucially introduced beforehand in the temperature equation so that the approximate initial data satisfying the corresponding compatibility conditions can be constructed. To overcome the strong coupling effect between the Euler part and the Fourier part in solving the linearized approximate problem, we further regularize the temperature equation by a pseudoparabolic equation. Moreover, we prove the uniform estimates with respect to the Mach number of the solutions to the free-boundary Euler-Fourier system with large temperature variations for the well-prepared initial data,which allow us to justify the convergence towards the free-boundary inviscid low Mach number limit system by the strong compactness argument.展开更多
This paper is devoted to devising data-driven algorithms for finite-horizon and infinite-horizon linear quadratic stochastic optimal control(LQSOC)problems.In our study,the diffusion terms of system dynamics are permi...This paper is devoted to devising data-driven algorithms for finite-horizon and infinite-horizon linear quadratic stochastic optimal control(LQSOC)problems.In our study,the diffusion terms of system dynamics are permitted to hinge upon both control and state variables,and the weighting matrices of cost functionals are allowed to be indefinite.It is acknowledged that the optimal controls of finite-horizon and infinite-horizon indefinite LQSOC problems are correlated with a generalized differential Riccati equation(GDRE)and a generalized algebraic Riccati equation(GARE).Herein,we propose two data-driven algorithms to approximate the solutions of these Riccati equations,and thereby determine optimal controls,without leveraging the information of all system parameters.Additionally,we prove the convergence of these algorithms and examine the impact of computational errors.Finally,we validate the performance of these data-driven algorithms via three simulation examples.展开更多
this paper,we establish the a priori estimates for solutions of mixed Hessian quotient type equations on Sn.Then we obtain the existence and uniqueness of Γk-admissible solutions to the Lp dual Minkowski type p...this paper,we establish the a priori estimates for solutions of mixed Hessian quotient type equations on Sn.Then we obtain the existence and uniqueness of Γk-admissible solutions to the Lp dual Minkowski type problem with p≥q.Moreover,we show the existence of convex solutions by Constant Rank Theorem.展开更多
THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-...THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4].展开更多
Generalised reduced masses with a set of equations governing the three relative motions between two of 3-bodies in their gravitational field are established,of which the dynamic characteristics of 3-body dynamics,fund...Generalised reduced masses with a set of equations governing the three relative motions between two of 3-bodies in their gravitational field are established,of which the dynamic characteristics of 3-body dynamics,fundamental bases of this paper,are revealed.Based on these findings,an equivalent system is developed,which is a 2-body system with its total mass,constant angular momentum,kinetic and potential energies same as the total ones of three relative motions,so that it can be solved using the well-known theory of the 2-body system.From the solution of an equivalent system with the revealed characteristics of three relative motions,the general theoretical solutions of the 3-body system are obtained in the curve-integration forms along the orbits in the imaged radial motion space.The possible periodical orbits with generalised Kepler’s law are presented.Following the description and mathematical demonstrations of the proposed methods,the examples including Euler’s/Lagrange’s problems,and a reported numerical one are solved to validate the proposed methods.The methods derived from the 3-body system are extended to N-body problems.展开更多
Sensitivity of observational data is important in the study of Glacial Isostatic Adjustment(GIA).However,depending on whether sensitivity is used for the Inverse Problem or the Forward Problem,the final formulation an...Sensitivity of observational data is important in the study of Glacial Isostatic Adjustment(GIA).However,depending on whether sensitivity is used for the Inverse Problem or the Forward Problem,the final formulation and display of the sensitivity kernel will be different.Unfortunately,in the past,both perspectives give the same name to their quantity computed/displayed,and that has caused some confusion.To distinguish between the two,their perspective should be added to the names.This paper focuses only on the perspective of the Forward Problem where the input parameters are known.The Perturbation method has been successfully used in the computation of the sensitivity kernels of observations on 1D and 3D viscosity variations from the Forward perspective.One aim of this paper is to review and clarify the physics of the Perturbation method and bring out some important aspects of this method that have been misunderstood or neglected.Another aim is to present sensitivity kernels from the Perturbation method using 3D(both radially and laterally heterogeneous)Earth models with realistic ice history.These new results are now suitable for future comparison with those from new methods using the Forward perspective.Finally,the sensitivity computations for realistic ice histories on a 3D Earth is reviewed and used to search for optimal locations of new GIA observations.展开更多
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
摘要During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h2/(4√2),where h is the piecewise length.
基金National Research Foundation of Korea(No.2025-02303676)。
摘要An efficient and innovative method is presented for the stress-related structural topology optimization(TO)in coupled mechanical-pressure systems by leveraging flexible polygonal meshes.With a polytopal composite finite element approach,the volumetric locking in nearly incompressible materials is reduced.A fluid-flow-based model is built,in which a design-dependent pressure variable is introduced to capture the loading conditions within the system.The P-norm approach consolidates the stress metrics into a global measure,while the clustered regional scaling and adaptive techniques enhance the solutions for stress-limited cases.The primary contributions of this work include a novel framework for addressing the stress challenges in coupled mechanical-pressure systems via flow-based modeling,the adaptability to both compressible and nearly incompressible materials,and the compatibility with diverse mesh types,including triangular,quadrilateral,and polygonal elements.The numerical examples demonstrate,for the first time,optimized topologies for nearly incompressible materials under stress constraints in coupled mechanical-pressure environments,emphasizing the unique strength of this approach.
基金Natural Science Foundation of Beijing Municipality under Grant No.7232057。
摘要The global incidence of pediatric obesity has increased rapidly over the past few decades.Scientific evidence has repeatedly shown that behavioral and emotional challenges are frequently observed in children with overweight or obesity[1-2],as evidenced by a landmark case-control design study revealing that obese children have 7.15 times higher odds of developing mental health disorders in adolescence than their normal-weight peers[1].
基金supported by the National Key Research and Development Program of China(Grant No.2023YFB3309104)the National Natural Science Foundation of China(Grant Nos.11821202 and 123721222)+1 种基金the Science Technology Plan of Liaoning Province(Grant No.2023JH2/101600044)the 111 Project of China(Grant No.B14013).
摘要Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integrated with topology optimization,achieving significant attention and progress in large-scale problems.This work aims to investigate how much benefit can be obtained by combining parallel computing and machine learning techniques to enhance the efficiency of large-scale topology optimization algorithms.Accordingly,a parallel problem independent machine learning(PIML)-enhanced topology optimization method is proposed.The PIML model substantially reduces the dimension of the condensed stiffness matrix and its computational cost,and parallel computing reduces the workload per process and enables the application of a parallel multigrid solver.Besides,several techniques,such as matrix-free implementation,direct condensation of uniform coarse elements,and adjusting computational resource limits,have been developed to enhance computational efficiency.The weak scaling efficiency,strong scaling speedup,and maximum achievable efficiency of the proposed method are validated across multiple numerical examples,showing significant improvement in the tractable problem size and solution efficiency compared to traditional topology optimization algorithms.
摘要The proliferation of carrier aircraft and the integration of unmanned aerial vehicles(UAVs)on aircraft carriers present new challenges to the automation of launch and recovery operations.This paper investigates a collaborative scheduling problem inherent to the operational processes of carrier aircraft,where launch and recovery tasks are conducted concurrently on the flight deck.The objective is to minimize the cumulative weighted waiting time in the air for recovering aircraft and the cumulative weighted delay time for launching aircraft.To tackle this challenge,a multiple population self-adaptive differential evolution(MPSADE)algorithm is proposed.This method features a self-adaptive parameter updating mechanism that is contingent upon population diversity,an asynchronous updating scheme,an individual migration operator,and a global crossover mechanism.Additionally,comprehensive experiments are conducted to validate the effectiveness of the proposed model and algorithm.Ultimately,a comparative analysis with existing operation modes confirms the enhanced efficiency of the collaborative operation mode.
基金funded by National Natural Science Foundation of China(Nos.12402142,11832013 and 11572134)Natural Science Foundation of Hubei Province(No.2024AFB235)+1 种基金Hubei Provincial Department of Education Science and Technology Research Project(No.Q20221714)the Opening Foundation of Hubei Key Laboratory of Digital Textile Equipment(Nos.DTL2023019 and DTL2022012).
摘要Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.
基金supported by the National Science and Technology Major Project(2022ZD0119901)the National Natural Science Foundation of China under Grant(U2141234,62463004 and U24A20260)+1 种基金the Hainan Province Science and Technology Special Fund(ZDYF2024GXJS003)the Scientific Research Fund of Hainan University(KYQD(ZR)23025).
摘要Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN models are limited in their ability to actively suppress noise,which constrains their robustness and precision in solving time-varying problems.This paper introduces a novel active noise rejection ZNN(ANR-ZNN)design that enhances noise suppression by integrating computational error dynamics and harmonic behaviour.Through rigorous theoretical analysis,we demonstrate that the proposed ANR-ZNN maintains robust convergence in computational error performance under environmental noise.As a case study,the ANR-ZNN model is specifically applied to time-varying matrix inversion.Comprehensive computer simulations and robotic experiments further validate the ANR-ZNN's effectiveness,emphasising the proposed design's superiority and potential for solving time-varying problems.
基金supported by the National Science and Technology Council,Taiwan,under grant no.NSTC 114-2221-E-197-005-MY3.
摘要With the development of technology,diffusion model-based solvers have shown significant promise in solving Combinatorial Optimization(CO)problems,particularly in tackling Non-deterministic Polynomial-time hard(NP-hard)problems such as the Traveling Salesman Problem(TSP).However,existing diffusion model-based solvers typically employ a fixed,uniform noise schedule(e.g.,linear or cosine annealing)across all training instances,failing to fully account for the unique characteristics of each problem instance.To address this challenge,we present GraphGuided Diffusion Solvers(GGDS),an enhanced method for improving graph-based diffusion models.GGDS leverages Graph Neural Networks(GNNs)to capture graph structural information embedded in node coordinates and adjacency matrices,dynamically adjusting the noise levels in the diffusion model.This study investigates the TSP by examining two distinct time-step noise generation strategies:cosine annealing and a Neural Network(NN)-based approach.We evaluate their performance across different problem scales,particularly after integrating graph structural information.Experimental results indicate that GGDS outperforms previous methods with average performance improvements of 18.7%,6.3%,and 88.7%on TSP-500,TSP-100,and TSP-50,respectively.Specifically,GGDS demonstrates superior performance on TSP-500 and TSP-50,while its performance on TSP-100 is either comparable to or slightly better than that of previous methods,depending on the chosen noise schedule and decoding strategy.
摘要Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emotional intelligence,and perceived social support.This study examined how gender,relational trauma,attachment dimensions,resilience,and emotional intelligence contribute to the presence of somatic and eating difficulties in this population.Methods:The sample included 46 adolescents(63%female;ages 12–17,Mean=14.85,Standard Deviation(SD)=1.49)residing in child protection institutions in Uruguay.Participants completed self-report measures assessing childhood relational trauma(CaMir),attachment dimensions(anxiety and avoidance),resilience,emotional intelligence(adaptability and stress management),social support(MOS),and psychosocial adjustment(SENA subscales of somatization and eating problems).Using a fuzzy-set Qualitative Comparative Analysis(fsQCA)approach,distinct configurations of risk and protective factors associated with elevated levels of somatization and eating problems were identified.Results:Relational trauma and attachment anxiety showed moderate associations with both somatization and eating problems(r=0.52–0.57,p<0.01),whereas stress management was negatively associated with both outcomes(r=−0.37 to−0.47,p<0.05).FsQCA revealed multiple configurations of risk and protective factors explaining 81–90%of cases,with solution consistencies ranging from 0.83 to 0.87.Results suggest that relational trauma and attachment anxiety are key risk conditions,whereas resilience,emotional regulation,and perceived social support function as protective factors.Conclusions:Findings highlight the importance of considering multifactorial patterns of vulnerability and protection rather than single predictors and underscore the need for tailored interventions that strengthen resilience and emotional skills while addressing the impact of early relational trauma.
摘要The newly formulated non-Newtonian rivulet flows streaming down an inclined planar surface,with additional periodic perturbations arising from the application of the 2nd Stokes problem to the investigation of rivulet dynamics,are demonstrated in the current research.Hereby,the 2nd Stokes problem assumes that the surface,with a thin shared layer of the fluid on it,oscillates in a harmonic manner along the x-axis of the rivulet flow,which coincides with the main flow direction streaming down the underlying surface.We obtain the exact extension of the rivulet flow family,clarifying the structure of the pressure field,which fully absorbs the arising perturbation.The profile of the velocity field is assumed to be Gaussian-type with a non-zero level of plasticity.Hence,the absolutely non-Newtonian case of the viscoplastic flow solution,which satisfies the motion and continuity equations,is considered(with particular cases of exact solutions for pressure).The perturbed governing equations of motion for rivulet flows then result in the Riccati-type ordinary differential equation(ODE),describing the dynamics of the coordinate x(t).The approximated schematic dynamics are presented in graphical plots.
基金supported by the National Natural Science Foundation of China(11601525)the Natural Science Foundation of Hunan Province(2024JJ5412),the Changsha Municipal Natural Science Foundation(kq2402193).
摘要In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zero-points distribution of the solutions and separate the single valued analytic branch of the solutions with square roots,then convert the problem to a Riemann boundary value problem in variable exponent Lebesgue spaces and discuss the singularity of solutions at individual zeros belonging to curve.We consider two types of cases those where the coefficient is Hölder and those where it is piecewise Hölder.Then we solve the Hilbert boundary value problem with square roots in variable exponent Lebesgue spaces.By discussing the distribution of the odd-order zero-points for solutions and the method of symmetric extension,we convert the Hilbert problem to a Riemann boundary value problem.The equivalence of the transformation is discussed.Finally,we get the solvable conditions and the direct expressions of the solutions in variable exponent Lebesgue spaces.
基金Supported by the Natural Science Foundation of Guangxi Province(Grant Nos.2023GXNSFAA026067,2024GXN SFAA010521)the National Natural Science Foundation of China(Nos.12361079,12201149,12261026).
摘要Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.
基金supported by the Youth Science and Technology of Gansu Province(26JRRA493,24JRRA148)the Northwest Normal University Young Teachers Research Capacity Promotion Plan(NWNULKQN2027-19,NWNU-LKQN2024-22).
摘要Large language models(LLMs)have demonstrated considerable ability in solving various tasks via Chain-of-Thought(CoT)prompting,which has precipitated extensive research into their application for complex mathematical reasoning problems.However,current research on mathematical reasoning with CoT predominantly focuses on textual mathematical tasks,such as math word problems,while paying limited attention to multimodal geometric scenarios.To bridge this gap,we propose KG-HoT,a model that harnesses the generative and comprehension capabilities of Multimodal large language models(MLLMs)to enhance complex geometric problem-solving in multimodal systems.Our knowledge-grounded approach enables MLLMs to generate hybrid chains-of-thought operating on dual tracks—language-based reasoning and program-based reasoning—which serve as teaching signals for smaller models.Furthermore,we design an instruction tuning framework that trains these dual reasoning tracks collaboratively within a unified architecture,enabling mutual enhancement and efficient knowledge distillation for complex geometric problem solving.Extensive experimental results demonstrate that KG-HoT achieves superior performance compared to existing approaches on multiple geometry problem-solving benchmarks.
摘要Scientific computing has become a cornerstone of modern scientific discovery and engineering innovation.With the rapid advancement of computational power and numerical algorithms,problems that were once analytically intractable can now be studied through accurate simulations and large-scale numerical experiments.Scientific computing provides a bridge between mathematical theory,computational algorithms,and real-world engineering applications,enabling researchers to model complex phenomena such as fluid flow,structural deformation,wave propagation,stochastic processes,and nonlinear dynamical systems.The special issue entitled“Scientific Computing and Its Application to Engineering Problems”was conceived to bring together high-quality research contributions that demonstrate the role of computational mathematics in solving challenging engineering problems.The issue highlights both theoretical advances in numerical methods and their practical deployment in real-world engineering scenarios,with emphasis on robustness,computational efficiency,stability,and scalability.
基金supported by National Natural Science Foundation of China (Grant No.12031006)supported by National Natural Science Foundation of China (Grant Nos.12171401 and 12231016)。
摘要We consider the free boundary problem for the Euler-Fourier system that describes the motion of compressible, inviscid and heat-conducting fluids. The effect of surface tension is neglected and there is no heat flux across the free boundary. We prove the local well-posedness of the problem in Lagrangian coordinates under the Taylor sign condition. The solution is produced as the limit of solutions to a sequence of tangentially-smoothed approximate problems, where the so-called corrector is crucially introduced beforehand in the temperature equation so that the approximate initial data satisfying the corresponding compatibility conditions can be constructed. To overcome the strong coupling effect between the Euler part and the Fourier part in solving the linearized approximate problem, we further regularize the temperature equation by a pseudoparabolic equation. Moreover, we prove the uniform estimates with respect to the Mach number of the solutions to the free-boundary Euler-Fourier system with large temperature variations for the well-prepared initial data,which allow us to justify the convergence towards the free-boundary inviscid low Mach number limit system by the strong compactness argument.
基金supported in part by the National Key Research and Development Program of China(2022YFA1006100)the National Natural Science Foundation of China(61925306)the Natural Science Foundation of Shandong Province(ZR2019ZD42)。
摘要This paper is devoted to devising data-driven algorithms for finite-horizon and infinite-horizon linear quadratic stochastic optimal control(LQSOC)problems.In our study,the diffusion terms of system dynamics are permitted to hinge upon both control and state variables,and the weighting matrices of cost functionals are allowed to be indefinite.It is acknowledged that the optimal controls of finite-horizon and infinite-horizon indefinite LQSOC problems are correlated with a generalized differential Riccati equation(GDRE)and a generalized algebraic Riccati equation(GARE).Herein,we propose two data-driven algorithms to approximate the solutions of these Riccati equations,and thereby determine optimal controls,without leveraging the information of all system parameters.Additionally,we prove the convergence of these algorithms and examine the impact of computational errors.Finally,we validate the performance of these data-driven algorithms via three simulation examples.
基金supported by the NSFC(11971157,12426532,12571213).
摘要this paper,we establish the a priori estimates for solutions of mixed Hessian quotient type equations on Sn.Then we obtain the existence and uniqueness of Γk-admissible solutions to the Lp dual Minkowski type problem with p≥q.Moreover,we show the existence of convex solutions by Constant Rank Theorem.
基金partially supported by the National Natural Science Foundation of China(62293500,62293505,62233010,62503240)Natural Science Foundation of Jiangsu Province(BK20250679)。
摘要THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4].
摘要Generalised reduced masses with a set of equations governing the three relative motions between two of 3-bodies in their gravitational field are established,of which the dynamic characteristics of 3-body dynamics,fundamental bases of this paper,are revealed.Based on these findings,an equivalent system is developed,which is a 2-body system with its total mass,constant angular momentum,kinetic and potential energies same as the total ones of three relative motions,so that it can be solved using the well-known theory of the 2-body system.From the solution of an equivalent system with the revealed characteristics of three relative motions,the general theoretical solutions of the 3-body system are obtained in the curve-integration forms along the orbits in the imaged radial motion space.The possible periodical orbits with generalised Kepler’s law are presented.Following the description and mathematical demonstrations of the proposed methods,the examples including Euler’s/Lagrange’s problems,and a reported numerical one are solved to validate the proposed methods.The methods derived from the 3-body system are extended to N-body problems.
摘要Sensitivity of observational data is important in the study of Glacial Isostatic Adjustment(GIA).However,depending on whether sensitivity is used for the Inverse Problem or the Forward Problem,the final formulation and display of the sensitivity kernel will be different.Unfortunately,in the past,both perspectives give the same name to their quantity computed/displayed,and that has caused some confusion.To distinguish between the two,their perspective should be added to the names.This paper focuses only on the perspective of the Forward Problem where the input parameters are known.The Perturbation method has been successfully used in the computation of the sensitivity kernels of observations on 1D and 3D viscosity variations from the Forward perspective.One aim of this paper is to review and clarify the physics of the Perturbation method and bring out some important aspects of this method that have been misunderstood or neglected.Another aim is to present sensitivity kernels from the Perturbation method using 3D(both radially and laterally heterogeneous)Earth models with realistic ice history.These new results are now suitable for future comparison with those from new methods using the Forward perspective.Finally,the sensitivity computations for realistic ice histories on a 3D Earth is reviewed and used to search for optimal locations of new GIA observations.