期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到130,380篇文章
< 1 2 … 250 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Knee point-guided heterogeneous surrogate-assisted optimization for multi-objective coal gasification system 认领 引用
1
作者 Wenlu Li Nan Guo +5 位作者 Tiewei Shang Yueyang Sun Dapeng Li Xiaolong Gao Wei Xiong Junfei Qiao 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2026年第2期168-180,共13页
Coal gasificationtechnology plays a pivotal role in chemical production as a key process for efficiently converting coal into liquid fuels and chemical feedstocks.During gasification,high-temperature reactions generat... Coal gasificationtechnology plays a pivotal role in chemical production as a key process for efficiently converting coal into liquid fuels and chemical feedstocks.During gasification,high-temperature reactions generate syngas,and optimizing its operational parameters is essential for improving syngas quality,carbon efficiencyand liquid fuel yield.However,the intricate chemical reactions and heat transfer mechanisms in gasificationnecessitate costly simulations or experimental testing,making it an expensive multi-objective optimization problem.To address this challenge,this paper proposes a Knee Point-guided Heterogeneous Surrogate-assisted Evolutionary Algorithm(KG-HSEA)that integrates Kriging and Feedforward Neural Networks(FNN)to construct a heterogeneous surrogate model,leveraging their complementary strengths to reduce computational costs while maintaining predictive accuracy.By incorporating a knee point-guided search mechanism,the method prioritizes solutions that embody critical trade-offs among conflictingobjectives.Moreover,an adaptive sampling strategy combined with dual-archive management is employed to dynamically update the surrogate model,ensuring it adapts to unstable operating conditions while maintaining robust convergence-diversity balance in coal gasificationprocesses.Experimental results show that KG-HSEA achieved a 71.9% superiority rate with 23 optimal solutions out of 32 benchmark problems,highlighting its potential for efficientand feasible coal gasificationoptimization. 展开更多
关键词 Coal gasification Expensive multi-objective optimization Kriging Feedforward neural network(FNN) Knee point Model management
暂未订购 下载PDF
Environment-adaptive design of multilayer optical structures for surface polariton excitation via dynamic multi-objective optimization 认领 引用
2
作者 Ru Lei Lin Li +4 位作者 Yiqi Feng Ziyue Ren Kun Zhang Lixun Sun Ting Mei 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第5期267-279,共13页
The graphene±dielectric multilayer architecture constitutes a fundamental and widely utilized platform for sustaining surface polariton(SP)propagation.Owing to their extraordinary prospects in defence critical te... The graphene±dielectric multilayer architecture constitutes a fundamental and widely utilized platform for sustaining surface polariton(SP)propagation.Owing to their extraordinary prospects in defence critical technologies,including radar-absorbing stealth coatings,high-power microwave shielding,and ultrafast optical switching,SPs have attracted intense and sustained interest.In this study,we develop an environment-adaptive design framework that models wavelength variation as a dynamic environmental change and automatically adjusts the design parameters in response.Our method employs a dynamic multi-objective optimization algorithm augmented with a predictive transfer strategy,optimizing SP coupling efficiency,structural compactness,and fabrication feasibility.Using a population history prediction mechanism,the framework not only adaptively generates multilayer designs across the full visible spectrum without full re-initialization,but also retains and exploits knowledge of how environmental variations influence the distribution of optimal solutions.This enables rapid adjustment of the optimization direction when parameters such as wavelength,angle,or doping change,thus avoiding the need to restart the search from scratch.Comprehensive comparisons demonstrate outstanding robustness under continuous wavelength shifts.The optimized graphene-coated distributed Bragg reflector(DBR)stacks achieve near-perfect absorption(>98%)at each individual wavelength across the visible spectrum.This work not only provides theoretical guidance for SP excitation experiments,but also contributes to the optimization of polariton device design,which is crucial for enhancing the performance of defence-related optical systems. 展开更多
关键词 Distributed bragg reflectors Surface polariton Dynamic multi-objective optimization
暂未订购 下载PDF
Multi-objective topology optimization for cutout design in deployable composite thin-walled structures 认领 引用
3
作者 Hao JIN Ning AN +3 位作者 Qilong JIA Chun SHAO Xiaofei MA Jinxiong ZHOU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期674-694,共21页
Deployable Composite Thin-Walled Structures(DCTWS)are widely used in space applications due to their ability to compactly fold and self-deploy in orbit,enabled by cutouts.Cutout design is crucial for balancing structu... Deployable Composite Thin-Walled Structures(DCTWS)are widely used in space applications due to their ability to compactly fold and self-deploy in orbit,enabled by cutouts.Cutout design is crucial for balancing structural rigidity and flexibility,ensuring material integrity during large deformations,and providing adequate load-bearing capacity and stability once deployed.Most research has focused on optimizing cutout size and shape,while topology optimization offers a broader design space.However,the anisotropic properties of woven composite laminates,complex failure criteria,and multi-performance optimization needs have limited the exploration of topology optimization in this field.This work derives the sensitivities of bending stiffness,critical buckling load,and the failure index of woven composite materials with respect to element density,and formulates both single-objective and multi-objective topology optimization models using a linear weighted aggregation approach.The developed method was integrated with the commercial finite element software ABAQUS via a Python script,allowing efficient application to cutout design in various DCTWS configurations to maximize bending stiffness and critical buckling load under material failure constraints.Optimization of a classical tubular hinge resulted in improvements of 107.7%in bending stiffness and 420.5%in critical buckling load compared to level-set topology optimization results reported in the literature,validating the effectiveness of the approach.To facilitate future research and encourage the broader adoption of topology optimization techniques in DCTWS design,the source code for this work is made publicly available via a Git Hub link:http://gffzz188fe103f8f1460asn0q6pp0w6noc6b6c.ffgz.tsg.suse.edu.cn/jinhao-ok1/Topo-for-DCTWS.git. 展开更多
关键词 Composite laminates Deployable structures Multi-objective optimization Thin-walled structures Topology optimization
暂未订购 下载PDF
A multi-tie points-based method for retrieving of the Arctic thin sea ice thickness from SMOS 认领 引用
4
作者 LI Jiaxing ZHANG Shengkai +2 位作者 XIAO Feng GENG Tong LI Fei 《Advances in Polar Science》 CSCD 2026年第1期43-55,共13页
The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie poin... The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie point(STP).However,due to pronounced spatial heterogeneity in seawater and sea ice properties across the Arctic,the use of an STP often leads to regionally biased.To address this limitation,this study proposes a multi-tie point(MTP)sea ice thickness retrieval method based on SMOS brightness temperature and sea ice concentration time series.Multiple seawater and sea ice tie-point values are identified through point-by-point time series analysis,quality control,and statistical hypothesis testing,allowing spatial variability in radiometric properties to be explicitly considered.The MTP-based retrieval is applied to Arctic freeze-up conditions.Validation against independent SMOS thin sea ice thickness products shows that the MTP approach yields significantly reduced bias and root mean square error compared with the conventional STP method,with statistically significant improvements confirmed by paired t-tests.While retrieval accuracy stabilizes beyond a certain number of tie points,the preprocessing cost associated with tie-point selection increases substantially.Considering both accuracy and efficiency,the MTP framework provides a practical and robust approach for large-scale Arctic thin sea ice thickness retrieval and enables improved characterization of regional freezing processes and maximum ice thickness. 展开更多
关键词 SMOS single-tie point Arctic multi-tie point thin sea ice thickness
暂未订购 下载PDF
Multi-Objective Optimization of a Tapered Cathode Flow Channel in a Proton Exchange Membrane Fuel Cell 认领 引用
5
作者 Wei Dong Baoqi Guo +2 位作者 Weiwei Zhao Hui Jian Zhenzong He 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第2期115-133,共19页
This study explores the design of a tapered cathode flow channel in a proton exchange membrane fuel cell(PEMFC),leveraging artificial intelligence and multi-objective optimization techniques to attain an optimal confi... This study explores the design of a tapered cathode flow channel in a proton exchange membrane fuel cell(PEMFC),leveraging artificial intelligence and multi-objective optimization techniques to attain an optimal configuration.First,the influence of the channel height ratio and mass flow rate on PEMFC performance was systematically examined.The results reveal that decreasing the height ratio and increasing the mass flow rate lead to reduction in the standard deviation of current density,accompanied by a monotonic rise in pressure drop.The average current density initially rises before exhibiting a slight decline.Subsequently,a surrogate model based on a Backpropagation(BP)neural network was constructed,with height ratio and mass flow rate as input variables,to accurately predict the average current density,its standard deviation,and the channel pressure drop.The findings demonstrate that the BP-based surrogate model can reliably predict current density,its standard deviation,and channel pressure drop.The Mean Relative Errors(MREs)for current density,standard deviation,and pressure drop are 0.84%,1.44%,and 1.77%,respectively,with all coefficients of determination(R2)exceeding 0.999.Finally,Pareto optimal solutions for current density,standard deviation,and pressure drop of the tapered PEMFC were obtained through integration a multi-objective genetic algorithm.Results show that the optimized tapered PEMFC achieves the current density of 3141.41 A/m2,the standard deviation of 53.58 A/m2,and the channel pressure drop of 5.49 Pa.Compared with the conventional channel,the optimized PEMFC exhibits an 7.02%increase in current density and an 3.7%reduction in standard deviation,while maintaining the pressure drop within an acceptable range. 展开更多
关键词 PEMFC tapered flow channel current density multi-objective optimization
暂未订购 下载PDF
Multi-Objective Approach for Optimizing Production Parameters of Low-Permeability Oil Well to Enhance Energy Efficiency 认领 引用
6
作者 LIU Peijin DING Haojian +3 位作者 YAN Dongyang SUN Haofeng HUANG Tao LI Jie 《Journal of Shanghai Jiaotong university(Science)》 EI 2026年第2期486-498,共13页
Aiming at the practical problems of high energy consumption and low energy efficiency during the exploitation of low-permeability oil wells because of insufficient traceability and poor matching performance of product... Aiming at the practical problems of high energy consumption and low energy efficiency during the exploitation of low-permeability oil wells because of insufficient traceability and poor matching performance of production parameters,this paper proposes a multi-objective approach for optimizing production parameters of low-permeability oil well to enhance its energy efficiency.First,a sub-model of daily liquid production yield and a sub-model of unit production energy consumption cost for single low-permeability oil well were established,and the Gaussian mixture model method was employed to compensate for the errors in the sub-model of unit production energy consumption cost,to solve the problem of the influence of uncertain facts during the oil well exploitation and to improve the precision of the model.Second,a multi-objective optimization model was established by taking into account the decision variables and constraints of the model,to maximize the daily liquid production yield while minimizing the unit production energy consumption cost.Subsequently,the non-dominated sorting genetic algorithm was employed to solve the multi-objective optimization model and obtain the production parameters.Finally,the solution set with obvious features was taken as the production parameters and applied to the actual production verification of low-permeability oil wells in a certain oil production plant of the ChangQing Oilfield.The results showed an increase in oil well production yield,and a significant energy-saving effect,thereby verifying the effectiveness of the proposed model and optimization algorithm in this paper. 展开更多
关键词 low-permeability oil well production parameter model error compensation multi-objective optimization non-dominated genetic algorithm
暂未订购 下载PDF
Multi-objective optimization design of biomimetic porous scaffolds based on cancellous bone structure 认领 引用
7
作者 Sujing Tian He Gong +2 位作者 Xiang Zhang Jiazi Gao Liming Zhou 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期546-564,共19页
As age advances,accumulation of bone regeneration inhibitors in osteoporotic patients increases,resulting in larger bone defect areas and varying degrees of defects.When studying bone regeneration in osteoporotic bone... As age advances,accumulation of bone regeneration inhibitors in osteoporotic patients increases,resulting in larger bone defect areas and varying degrees of defects.When studying bone regeneration in osteoporotic bone defects,researchers often lack specificity on different bone quality statuses.To design a porous scaffold more similar to cancellous bone to promote bone regeneration,a multi-objective optimization design of biomimetic porous scaffold based on cancellous bone images was carried out in this study.Vertebral cancellous bones from rats with different bone quality statuses caused by various ovariectomy durations served as examples.First,the microstructure,mechanical and biological properties parameters of vertebral cancellous bones were calculated based on images from 20-,30-,and 38-week-old rats without ovariectomy and 30-and 38-week-old rats with ovariectomy(10 weeks and 18 weeks after ovariectomy).Second,the effects of constant value(C),which affects scaffold thickness,scale factor of z-axis(N),influencing stretching and compression of unit cell,and unit cell size(L)on the mechanical and biological properties of Schoen Gyroid and Schoen I-WP were investigated.Third,Schoen Gyroid and Schoen I-WP were optimized and evaluated using non-dominated genetic algorithm-II(NSGA-II)and complex proportional assessment method,with the elastic modulus of cancellous bones from 30-and 38-week-old ovariectomized rats as performance constraint to obtain the best structure tailored to each ovariectomized group.The surface curvature of the scaffold could be changed by stretching or compressing the unit cell,and the pore size could be changed by altering the unit cell thickness and size to obtain scaffolds suitable for different extents of bone defects.The optimized scaffolds met mechanical and biological requirements.Schoen I-WP exhibited superior comprehensive performance compared to Schoen Gyroid.The optimized design framework proposed in this study can be applied to bone defects of any age,bone site,and bone quality status,and has potential application for personalized treatment of bone defects. 展开更多
关键词 Osteoporotic bone defect Biomimetic porous scaffold Comprehensive performance Multi-objective optimization Complex proportional assessment method
暂未订购 下载PDF
Multi-objective spatial optimization by considering land use suitability in the Yangtze River Delta region 认领 引用
8
作者 CHENG Qianwen LI Manchun +4 位作者 LI Feixue LIN Yukun DING Chenyin XIAO Lishan LI Weiyue 《Journal of Geographical Sciences》 SCIE CSCD 2026年第1期45-78,共34页
Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method f... Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development.Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources.This study proposes an Ecological Security-Food Security-Urban Sustainable Development(ES-FS-USD)spatial optimization framework.This framework combines the non-dominated sorting genetic algorithm II(NSGA-II)and patch-generating land use simulation(PLUS)model with an ecological protection importance evaluation,comprehensive agricultural productivity evaluation,and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta(YRD)region in 2035.The proposed sustainable development(SD)scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits.The simulation results were further revised by evaluating the land-use suitability of the YRD region.According to the revised spatial pattern for the YRD in 2035,the farmland area accounts for 43.59%of the total YRD,which is 5.35%less than that in 2010.Forest,grassland,and water area account for 40.46%of the total YRD—an increase of 1.42%compared with the case in 2010.Construction land accounts for 14.72%of the total YRD—an increase of 2.77%compared with the case in 2010.The ES-FS-USD spatial optimization framework ensures that spatial optimization outcomes are aligned with the natural endowments of land resources,thereby promoting the sustainable use of land resources,improving the ability of spatial management,and providing valuable insights for decision makers. 展开更多
关键词 multi-objective spatial optimization multi-scenario simulation ecological protection importance comprehensive agricultural productivity urban sustainable development land-use suitability
暂未订购 下载PDF
A Multi-Objective Deep Reinforcement Learning Algorithm for Computation Offloading in Internet of Vehicles 认领 引用
9
作者 Junjun Ren Guoqiang Chen +1 位作者 Zheng-Yi Chai Dong Yuan 《Computers, Materials & Continua》 SCIE EI 2026年第1期2111-2136,共26页
Vehicle Edge Computing(VEC)and Cloud Computing(CC)significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrain... Vehicle Edge Computing(VEC)and Cloud Computing(CC)significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrained onboard devices to nearby Roadside Unit(RSU),thereby achieving lower delay and energy consumption.However,due to the limited storage capacity and energy budget of RSUs,it is challenging to meet the demands of the highly dynamic Internet of Vehicles(IoV)environment.Therefore,determining reasonable service caching and computation offloading strategies is crucial.To address this,this paper proposes a joint service caching scheme for cloud-edge collaborative IoV computation offloading.By modeling the dynamic optimization problem using Markov Decision Processes(MDP),the scheme jointly optimizes task delay,energy consumption,load balancing,and privacy entropy to achieve better quality of service.Additionally,a dynamic adaptive multi-objective deep reinforcement learning algorithm is proposed.Each Double Deep Q-Network(DDQN)agent obtains rewards for different objectives based on distinct reward functions and dynamically updates the objective weights by learning the value changes between objectives using Radial Basis Function Networks(RBFN),thereby efficiently approximating the Pareto-optimal decisions for multiple objectives.Extensive experiments demonstrate that the proposed algorithm can better coordinate the three-tier computing resources of cloud,edge,and vehicles.Compared to existing algorithms,the proposed method reduces task delay and energy consumption by 10.64%and 5.1%,respectively. 展开更多
关键词 Deep reinforcement learning internet of vehicles multi-objective optimization cloud-edge computing computation offloading service caching
暂未订购 下载PDF
Sustainability evaluation of novel side-stream extractive distillation incorporating intermediate reboiler process for recovering ethyl acetate and methanol from wastewater based on multi-objective optimization 认领 引用
10
作者 Ruimin Zhang Shuang Yang +3 位作者 Jinlong Li Hui Wang Tan Dai Qing Ye 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2026年第2期232-248,共17页
Although side-stream extractive distillation(SED)is widely applied in azeotropic mixture separation due to its high efficiencyand energy-saving advantages,the use of expensive high-pressure steam increases economic co... Although side-stream extractive distillation(SED)is widely applied in azeotropic mixture separation due to its high efficiencyand energy-saving advantages,the use of expensive high-pressure steam increases economic costs.The introduction of intermediate reboiler(IR)can reduce the consumption of high-pressure steam and thus reduce the operating cost.This work selects the extractive distillation process,using dimethyl sulfoxide(DMSO)as the solvent to separate ethyl acetate and methanol from wastewater.Based on the system characteristics,two SED processes are designed:SED-1 process directly obtains high-purity DMSO from the bottom of the SED column,whereas SED-2 process obtains a DMSO/water mixture at the bottom.To reduce high-pressure steam requirements,an IR is incorporated,leading to the proposal of SED-IR-1 and SED-IR-2 processes.Finally,heat-integrated processes(H-SEDIR-1 and H-SED-IR-2)are proposed based on the optimal SED-IR-1 and SED-IR-2 processes,which utilized the solvent stream waste heat to heat the IR to further reduce the energy consumption and operating cost.The results demonstrate that the H-SED-IR-1 process exhibits optimal economic performance with a 26.19% reduction in total annual cost compared with the conventional extractive distillation(CED)process,while the innovative H-SED-IR-2 process shows outstanding environmental benefits,achieving 38.78% and 39.97% reductions in CO2emissions and entropy generation,respectively,compared to the CED process. 展开更多
关键词 Ternary system with double binary azeotropes Side-stream extractive distillation Intermediate reboiler Multi-objective optimization Heat integration technology
暂未订购 下载PDF
Multi-objective land use simulation by integrating urban spatial suitability and ecological carrying capacity evaluations 认领 引用
11
作者 CHEN Zeyin LI Siying +3 位作者 LIU Zheng HUO Yixin WU Tao ZHOU Xingang 《Journal of Geographical Sciences》 SCIE CSCD 2026年第4期799-824,共26页
Balancing urbanization with ecological carrying capacity is essential for sustainable urban development.Traditional land use prediction and urban growth boundary(UGB)delineation methods often overlook ecological asses... Balancing urbanization with ecological carrying capacity is essential for sustainable urban development.Traditional land use prediction and urban growth boundary(UGB)delineation methods often overlook ecological assessments and fail to address policy conflicts.This study proposes an integrated model combining urban spatial suitability(USS)and ecological carrying capacity(ECC)evaluations with cellular automata(CA)model to improve simulation accuracy and support scenario-based UGB delineation.First,we identify spatial variations in urban development potential under different scenarios by adjusting the weights of USS and ECC.Then,a multi-objective planning model is used to optimize the future land-use structure,maximizing overall benefits.Finally,the development potential and optimized land allocation are incorporated into the CA model to simulate future land use and delineate UGB for each scenario.Results show that integrating USS and ECC evaluations improves simulation accuracy,with the Kappa coefficient increasing from 0.836(with only USS evaluation)to 0.908 and overall accuracy reaching 94.1%.While the economic development scenario yields the highest economic benefits,a stronger emphasis on ECC produces more compact and spatially organized urban forms,characterized by higher aggregation and lower fragmentation.This framework provides a robust basis for multi-scenario urban simulation and offers valuable guidance for the scientific UGB delineation. 展开更多
关键词 land use prediction urban growth boundary cellular automata multi-scenario simulation urban spatial suitability ecological carrying capacity multi-objective planning
暂未订购 下载PDF
Hybrid Flow Shop Rescheduling Approach Based on Hybrid-Driven Mechanism and Improved Multi-Objective WOA 认领 引用
12
作者 Feng Lv Xin Xu +1 位作者 Cheng Yang Yixuan Tang 《Computers, Materials & Continua》 SCIE EI 2026年第7期1982-2009,共28页
To ensure an effective disturbance response and maintain continuous production in hybrid flow shops,this paper focuses on the design of a rescheduling method.A rescheduling model is constructed that minimizes the make... To ensure an effective disturbance response and maintain continuous production in hybrid flow shops,this paper focuses on the design of a rescheduling method.A rescheduling model is constructed that minimizes the makespan,total tardiness,and scheme deviation degree.A hybrid rescheduling driving mechanism based on the latest completion time is designed to effectively trigger rescheduling.The Whale Optimization Algorithm(WOA)is improved by integrating the good point set theory,nonlinear control parameter strategy,and Differential Evolution(DE)algorithm.Moreover,non-dominated sorting and a dynamic external archive mechanism based on crowding distance are introduced to make it suitable for multi-objective optimization problems.The superiority of the Improved Multi-objective Whale Optimization Algorithm(IMOWOA)and the effectiveness of the improved mechanisms are verified through comparative experiments and ablation experiments.Taking the final assembly production line of an agricultural machinery equipment enterprise as an example,a rescheduling scheme is generated based on the practical production requirements,which verifies the feasibility and effectiveness of the proposed method. 展开更多
关键词 Hybrid flow shop production disturbance production rescheduling rescheduling driving mechanism improved multi-objective whale optimization algorithm
暂未订购 下载PDF
CMo-IABA:Constrained Multi-Objective Invisible and Adaptive Backdoor Attack for Deep Neural Networks-Based SAR Image Classification 认领 引用
13
作者 Guo-Qiang Zeng Hai-Nan Wei +1 位作者 Kang-Di Lu Guang-Gang Geng 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第7期1731-1746,共16页
Deep neural networks(DNNs)have been widely applied in the field of synthetic aperture radar(SAR)image while they are facing more and more serious threats from a variety of malicious attacks.As one of the malicious att... Deep neural networks(DNNs)have been widely applied in the field of synthetic aperture radar(SAR)image while they are facing more and more serious threats from a variety of malicious attacks.As one of the malicious attacks with strong destructiveness and stealth,backdoor attacks have severely affected DNNs,but there are no related research studies concerning the backdoor attacks against the DNNs-based SAR image classification models.In this work,we make the first attempt to automatically design a constrained multi-objective invisible and adaptive backdoor attack termed as CMo-IABA for DNNs-based SAR image classification.In the CMo-IABA,we firstly generate an initial trigger-based backdoor attack randomly by a random combination of pixels with random noise conforming to the Gaussian distribution.Then,we design multi-objective functions by considering the trade-off between maximizing the attack success rate and minimizing L2 distance-based invisibility.The classification error between the backdoor DNN and the clean model is considered as the constraint to maintain the original performance of the model.To solve the optimization problem,a discrete non-dominated sorting genetic algorithm-II is introduced as the search engine with the developed crossover operation and mutation operation.The superiority of the proposed CMo-IABA to five state-of-the-art backdoor attacks on six different types of DNNs-based SAR image classification models has been demonstrated by the experimental results on Fudan University SAR(FUSAR)-ship and moving and stationary target acquisition and recognition(MSTAR)datasets in terms of attack success rate and L2 distance-based invisibility. 展开更多
关键词 Backdoor attack constrained multi-objective optimization deep neural network(DNN) image classification invisibility synthetic aperture radar
暂未订购 下载PDF
Multi-objective integrated cotton cultivation(MOICC):A synergistic framework for sustainable production 认领 引用
14
作者 Yanjun Zhang Jianlong Dai Hezhong Dong 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2026年第4期1316-1329,共14页
Global cotton production faces mounting pressure to reconcile rising fiber demand with urgent sustainability imperatives,including water scarcity mitigation,greenhouse gas reduction,and agrochemical pollution control.... Global cotton production faces mounting pressure to reconcile rising fiber demand with urgent sustainability imperatives,including water scarcity mitigation,greenhouse gas reduction,and agrochemical pollution control.Traditional practices,constrained by fragmented objectives and inherent trade-offs among yield,fiber quality,labor efficiency,and ecological impact,struggle to address these systemic challenges.Building upon previous concept of collaborative cultivation,this review for the first time introduces and comprehensively elaborates multi-objective integrated cotton cultivation(MOICC)-also referred to as integrated cotton cultivation(ICC)-a transformative framework centered on three pillars:dynamic tradeoff management(e.g.,region-specific priority adjustment),systematic technology integration(precision seeding,dense planting,chemical regulation,water-nutrient synergy,and targeted defoliation),and resource circularity(spatiotemporal optimization and waste recycling).MOICC overcomes sustainability bottlenecks by leveraging key physiological mechanisms,including ethylene signaling to enhance stress-resilient seedling establishment,jasmonate-mediated pathways to improve waterutrient efficiency,canopy light competition coupled with hormonal regulation to eliminate manual pruning,and growth regulators to concentrate boll maturation.Case studies from diverse Chinese agro-ecosystems(e.g.,Xinjiang,Yangtze/Yellow River basins)and intercropping systems demonstrate significant synergies:increased yield(8-22%),improved resource efficiency(water use efficiency increased by≥20%,and nitrogen productivity up to 35 kg kg-1),and enhanced environmental performance(labor reduction of 30-40%,carbon footprint reduction of 24-37%,and agrochemical savings:nitrogen reduction of 15-20%and pesticides reduction of 25%).Crucially,MOICC resolves core conflicts through integrated optimization:yield vs.quality(via≥70%inner-position bolls),labor-saving vs.eco-safety(precision defoliant timing),and productivity vs.emissions(root-zone nitrogen monitoring).Future research priorities include deciphering multi-scale stress adaptation,developing intelligent decision-support systems(e.g.,AHP-NSGA-II integration),advancing carbon-neutral value chains,addressing socio-economic adoption barriers,and fostering policy synergy.Overall,MOICC establishes a conceptually globally scalable pathway toward high-yield,superior-quality,resource-efficient,and ecologically sustainable cotton production,with potential applicability to other major cropping systems. 展开更多
关键词 cotton(Gossypium hirsutum L.) multi-objective integrated cultivation sustainable agriculture resource-use efficiency technology synergy
暂未订购 下载PDF
Boundary Decision-Based Multi-Objective Robust Optimization for Microgrid Dispatching 认领 引用
15
作者 Junjian Wu Jingliao Sun +2 位作者 Yejun Xiang Zhenyu Zhou Zhengchai Shi 《Energy Engineering》 EI 2026年第7期404-423,共20页
The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids.In response,this paper proposes a novel robust optimization ... The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids.In response,this paper proposes a novel robust optimization strategy grounded in uncertain boundary decision-making and enhanced through innovations in the multi-objective cross-entropy method.An uncertainty budget-aware environmental economic dispatch model is first established,integrating photovoltaic and wind power generation.By employing mathematical sophistication-particularly Lagrangian transformation-the proposed method effectively resolves embedded uncertainties,transforming the original model into a deterministic multi-objective optimization framework robust against renewable energy volatility.Furthermore,by incorporating the dynamic operational demands of microgrids,this paper culminates in a robust optimization approach that is both fundamentally based on and adaptively responsive to uncertainty boundaries.To address the critical challenges of convergence and diversity in multi-objective optimization,crossover operators and an adaptive parameter update mechanism are introduced,significantly refining the conventional multi-objective cross-entropy algorithm.Case studies demonstrate the rationality and effectiveness of the proposed dispatch strategy and corroborate the superior performance and applicability of the enhanced algorithm. 展开更多
关键词 Microgrid environmental economic dispatch uncertain boundary robust optimization multi-objective cross entropy algorithm
暂未订购 下载PDF
Exploring the mechanism of myofascial trigger points deactivation by Tuina via the TGF-β1/Smad3 signaling pathway 认领 引用
16
作者 Liya Tang Xiaowei Liu +4 位作者 Jiadong Zang Yuqiao Zhang Xiang Feng Wu Li Jiangshan Li 《Digital Chinese Medicine》 CAS CSCD 2026年第1期103-113,共11页
Objective To investigate whether Tuina alleviates fibrotic symptoms in myofascial trigger points(MTrPs)by regulating transforming growth factor(TGF)-β1/Smad3 signaling pathway,thereby deactivating these points.Method... Objective To investigate whether Tuina alleviates fibrotic symptoms in myofascial trigger points(MTrPs)by regulating transforming growth factor(TGF)-β1/Smad3 signaling pathway,thereby deactivating these points.Methods This study comprised two experimental phases.In phase 1,27 specific pathogenfree(SPF)grade female Sprague-Dawley(SD)rats were randomized into three groups:control 1,model 1,and Tuina 1 groups.Model 1 and Tuina 1 groups underwent an 8-week MTrPs modeling protocol involving blunt impact and eccentric exercise.After successful modeling,rats in Tuina 1 group received manual pressing on nodules or cord-like taut bands on the medial aspect of the left hindlimb.Pain sensitivity and tissue stiffness were evaluated via pressure pain threshold(PPT)and soft tissue tension(STT).Muscle histopathology and fibrosis were observed using hematoxylin and eosin(HE)and Masson staining.Inflammatory factors in muscle were measured by enzyme-linked immunosorbent assay(ELISA),while immunofluorescence(IF)and Western blot(WB)were used to detect the expression levels ofα-smooth muscle actin(α-SMA),collagenⅢ,and TGF-β1.In phase 2,45 SPF female SD rats were randomized into five groups:control 2,model 2,Tuina 2,TGF-β1 inhibitor(TI),and Tuina+TGF-β1 agonist(Tuina+TA)groups.All groups except control 2 underwent standardized MTrPs modeling.Rats in Tuina 2 group received consistent pressing manipulation.TI group received intraperitoneal injections of oxymatrine,while Tuina+TA group received intraperitoneal injections of SRI-011381 hydrochloride followed by the same pressing protocol as Tuina 2 group.WB was used to detect the expression of collagen I,collagen III,TGF-β1,and phosphorylated-Smad3(p-Smad3)/Smad3.Results In phase 1,Tuina significantly improved PPT and STT in MTrPs of rats(P<0.01),reversed pathological damages including disorganized muscle fiber arrangement,abnormal myocyte morphology,and exacerbated fibrosis.In addition,in MTrPs of rats in model 1 group,expression levels of nuclear factor kappa-light-chain-enhancer of activated B cells(NF-κB),interleukin(IL)-1β,IL-6,tumor necrosis factor(TNF)-α,and fibrosis markers(α-SMA,collagen I,and collagen III)were upregulated,and all exhibited a significant downward trend after Tuina intervention(P<0.05 or P<0.01).This indicates that the therapeutic effects of Tuina are directly associated with reduced local inflammation and fibrosis in MTrPs.In phase 2,compared with model 2 group,rats in TI and Tuina 2 groups had decreased expression levels of TGF-β1 and p-Smad3/Smad3 in MTrPs,alongside reduced levels of inflammatory factors(IL-1β,IL-6,NF-κB,and TNF-α)and fibrosis markers(α-SMA,collagen I,and collagen III)(P<0.05 or P<0.01).When co-administered with TGF-β1 agonist,the therapeutic effects of Tuina were significantly attenuated,with rebounded TGF-β1 expression and p-Smad3/Smad3 in local MTrPs,and fibrosis and inflammatory responses were re-exacerbated(P<0.05 or P<0.01).Conclusion Tuina can effectively reduce inflammatory responses and fibrosis in MTrPs tissue,and its mechanism is closely related to the inhibition of the TGF-β1/Smad3 signaling pathway,which plays a critical role in Tuina-mediated regulation of MTrPs fibrosis. 展开更多
关键词 Tuina Pressing Inflammation Myofascial trigger points Fibrosis TGF-β1 p-Smad3
暂未订购 下载PDF
Orbital parameter characterization and objects cataloging for Earth-Moon collinear libration points 认领 引用
17
作者 Chenyuan QIAO Xi LONG +2 位作者 Leping YANG Yanwei ZHU Peng WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期551-566,共16页
Owing to the chaotic and non-integrable nature of three-body dynamics,the conventional Keplerian elements are rendered inadequate for cataloging cislunar space objects.Currently,there has been a conspicuous absence of... Owing to the chaotic and non-integrable nature of three-body dynamics,the conventional Keplerian elements are rendered inadequate for cataloging cislunar space objects.Currently,there has been a conspicuous absence of universally recognized parameters for the characterization and cataloging of such objects,thereby posing an urgent challenge to cislunar space situational awareness.This paper proposes a novel approach to parameterize the orbits of Earth-Moon collinear libration points by leveraging the theoretical frameworks of canonical transformations.First,under the Hamiltonian-form dynamical equations of the libration point,symplectic transformations are employed to extract 3 modes of motion from locally linearized part.A subsequent canonical transformation then decouples the hyperbolic invariant manifold from the center manifold within the nonlinear remainder.Finally,6 characteristic parameters obtained via action-angle variables are established in a bijective correspondence with the state variables,where two parameters characterize the motion of the invariant manifold and four parameters characterize the motion of the central manifold.Furthermore,a distribution map of the Earth-Moon libration point orbits is drawn utilizing Poincare sections,which can be used to describe the distribution of libration point object.Simulation results demonstrate that the proposed parameters are not only applicable to orbit identification and object cataloging but also exhibit remarkable consistency and robustness against variations in observation arc length and observational errors. 展开更多
关键词 Canonical transformation Characteristic parameters Cislunar space Collinear libration points Objects cataloging Orbital calculations Spacecraft
暂未订购 下载PDF
Multi-objective trajectory optimization for spaceborne antennas with nonlinear coupling using hp-adaptive pseudospectral discretization 认领 引用
18
作者 Feng GAO Guanghui SUN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第2期517-530,共14页
Spaceborne antennas are essential for remote sensing,deep-space communication,and Earth observation,yet their trajectory planning is complicated by nonlinear base-manipulator coupling and antenna flexibility.To addres... Spaceborne antennas are essential for remote sensing,deep-space communication,and Earth observation,yet their trajectory planning is complicated by nonlinear base-manipulator coupling and antenna flexibility.To address these challenges,this paper proposes a multi-objective trajectory optimization framework.The system dynamics capture both nonlinear rigid-flexible coupling and antenna deformation through a reduced-order formulation.To enhance discretization efficiency,a predictive-terminal hp-adaptive pseudospectral method is employed,assigning collocation density based on task-phase characteristics:finer resolution is applied to dynamic segments requiring higher accuracy,especially near the terminal phase.This enables efficient transcription of the continuous-time problem into a Nonlinear Programming Problem(NLP).The resulting NLP is then solved using a multi-objective optimization strategy based on the nondominated sorting genetic algorithm II,which explores trade-offs among antenna pointing accuracy,energy consumption,and structural vibration.Numerical results demonstrate that the proposed method achieves a reduction of approximately 14.0% in control energy and 41.8%in peak actuation compared to a GPOPS-II baseline,while significantly enhancing vibration suppression.The resulting Pareto front reveals structured trade-offs and clustered solutions,offering robust and diverse options for precision,low-disturbance mission planning. 展开更多
关键词 hp-adaptive pseudospectral method Multi-objective trajectory optimization Nonlinear dynamics Rigid-flexible coupling Spaceborne antenna Structural vibration suppression
暂未订购 下载PDF
Research framework for scientific innovation and translational application of original acupuncture theories:a review based on Hand Twelve Jing-Well Points stimulation therapy 认领 引用
19
作者 Yu Luo Zheng Zhu +10 位作者 Feifei Gao Dan Zhou Ningcen Li Zhongxi Lyu Liang Zhou Siru Qin Yuanzhen Yang Baoming Dou Ning Ma Yi Guo Zhifang Xu 《Acupuncture and Herbal Medicine》 CAS CSCD 2026年第1期42-55,共14页
The field of acupuncture is currently facing paradigmatic issues,including the difficulty of turning theoretical strengths into technical discourse power,a gap between mechanistic research and clinical imperatives,and... The field of acupuncture is currently facing paradigmatic issues,including the difficulty of turning theoretical strengths into technical discourse power,a gap between mechanistic research and clinical imperatives,and the fragmentation of research activities.Therefore,constructing a research paradigm grounded in traditional Chinese medicine theory and validated through contemporary scientific methods is essential.Hand Twelve Jing-Well Points(HTWP)acupuncture,an ancient therapy known for its rapid efficacy and practical application,offers an optimal solution for these challenges.In this study,the theoretical foundations,clinical effectiveness,biological explanations,and Translational applications of HTWP acupuncture were consolidated by integrating a four-step research framework.Initially,we developed the“Well point-Brain Connection”framework rooted in classical theories and informed by the“Root-Knot”concept.Subsequent clinical practice provided evidence of its effectiveness in modulating awareness and facilitating motor-cognitive rehabilitation for patients with central nervous system issues.Moreover,mechanistic research provides scientific verification of a“Sensation-Transmission-Effect”cascade that encompasses the activation of arousal circuits and the repair of the blood-brain barrier.Ultimately,the promotion of translation,standardization of systems,and the use of wearable technologies have aided the transition from passive therapy to proactive health management.This closed-loop concept offers compelling evidence for the“Well point-Brain Connection”and provides an applicable framework for scientific innovation and global distribution of innovative acupuncture hypotheses. 展开更多
关键词 Acupuncture Central nervous system diseases Hand Twelve Jing-Well Points Research paradigm Translational medicine Well point-brain connection
暂未订购 下载PDF
An intelligent segmentation method for leakage points in central serous chorioretinopathy based on fluorescein angiography images 认领 引用
20
作者 Jian-Guo Xu Yong-Chi Liu +4 位作者 Fen Zhou Jian-Xin Shen Zhi-Peng Yan Xin-Ya Hu Wei-Hua Yang 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2026年第3期421-433,共13页
AIM:To construct an intelligent segmentation scheme for precise localization of central serous chorioretinopathy(CSC)leakage points,thereby enabling ophthalmologists to deliver accurate laser treatment without navigat... AIM:To construct an intelligent segmentation scheme for precise localization of central serous chorioretinopathy(CSC)leakage points,thereby enabling ophthalmologists to deliver accurate laser treatment without navigational laser equipment.METHODS:A dataset with dual labels(point-level and pixel-level)was first established based on fundus fluorescein angiography(FFA)images of CSC and subsequently divided into training(102 images),validation(40 images),and test(40 images)datasets.An intelligent segmentation method was then developed,based on the You Only Look Once version 8 Pose Estimation(YOLOv8-Pose)model and segment anything model(SAM),to segment CSC leakage points.Next,the YOLOv8-Pose model was trained for 200 epochs,and the best-performing model was selected to form the optimal combination with SAM.Additionally,the classic five types of U-Net series models[i.e.,U-Net,recurrent residual U-Net(R2U-Net),attention U-Net(AttU-Net),recurrent residual attention U-Net(R2AttUNet),and nested U-Net(UNet++)]were initialized with three random seeds and trained for 200 epochs,resulting in a total of 15 baseline models for comparison.Finally,based on the metrics including Dice similarity coefficient(DICE),intersection over union(IoU),precision,recall,precisionrecall(PR)curve,and receiver operating characteristic(ROC)curve,the proposed method was compared with baseline models through quantitative and qualitative experiments for leakage point segmentation,thereby demonstrating its effectiveness.RESULTS:With the increase of training epochs,the mAP50-95,Recall,and precision of the YOLOv8-Pose model showed a significant increase and tended to stabilize,and it achieved a preliminary localization success rate of 90%(i.e.,36 images)for CSC leakage points in 40 test images.Using manually expert-annotated pixel-level labels as the ground truth,the proposed method achieved outcomes with a DICE of 57.13%,an IoU of 45.31%,a precision of 45.91%,a recall of 93.57%,an area under the PR curve(AUC-PR)of 0.78 and an area under the ROC curve(AUC-ROC)of 0.97,which enables more accurate segmentation of CSC leakage points.CONCLUSION:By combining the precise localization capability of the YOLOv8-Pose model with the robust and flexible segmentation ability of SAM,the proposed method not only demonstrates the effectiveness of the YOLOv8-Pose model in detecting keypoint coordinates of CSC leakage points from the perspective of application innovation but also establishes a novel approach for accurate segmentation of CSC leakage points through the“detect-then-segment”strategy,thereby providing a potential auxiliary means for the automatic and precise realtime localization of leakage points during traditional laser photocoagulation for CSC. 展开更多
关键词 You Only Look Once version 8 Pose Estimation segment anything model central serous chorioretinopathy leakage point segmentation
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 250 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈