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A Hybrid Improved Genetic Algorithm and Its Application in Dynamic Optimization Problems of Chemical Processes 认领 引用 被引量：5
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作者 SUN Fan DU Wenli +2 位作者 QI Rongbin QIAN Feng ZHONG Weimin 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2013年第2期144-154,共11页
The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature.13enetic algorithm(GA)has been proved to be a teasibte method when the gradient is di... The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature.13enetic algorithm(GA)has been proved to be a teasibte method when the gradient is difficult to calculate.Its advantage is that the control profiles at all time stages are optimized simultaneously,but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum.In this study,a hybrid improved genetic algorithm(HIGA)for solving dynamic optimization problems is proposed to overcome these defects.Simplex method(SM)is used to perform the local search in the neighborhood of the optimal solution.By using SM,the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved.The hybrid algorithm presents some improvements,such as protecting the best individual,accepting immigrations,as well as employing adaptive crossover and Ganssian mutation operators.The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems.At last,HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable. 展开更多
关键词 genetic algorithm simplex method dynamic optimization chemical process
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A Hybrid Immigrants Scheme for Genetic Algorithms in Dynamic Environments 认领 引用 被引量：11
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作者 Shengxiang Yang Renato Tinós 《International Journal of Automation and computing》 2007年第3期243-254,共12页
Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the ... Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution（s） of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interest from the genetic algorithm community in recent years. Several approaches have been developed to enhance the performance of genetic algorithms in dynamic environments. One approach is to maintain the diversity of the population via random immigrants. This paper proposes a hybrid immigrants scheme that combines the concepts of elitism, dualism and random immigrants for genetic algorithms to address dynamic optimization problems. In this hybrid scheme, the best individual, i.e., the elite, from the previous generation and its dual individual are retrieved as the bases to create immigrants via traditional mutation scheme. These elitism-based and dualism-based immigrants together with some random immigrants are substituted into the current population, replacing the worst individuals in the population. These three kinds of immigrants aim to address environmental changes of slight, medium and significant degrees respectively and hence efficiently adapt genetic algorithms to dynamic environments that are subject to different severities of changes. Based on a series of systematically constructed dynamic test problems, experiments are carried out to investigate the performance of genetic algorithms with the hybrid immigrants scheme and traditional random immigrants scheme. Experimental results validate the efficiency of the proposed hybrid immigrants scheme for improving the performance of genetic algorithms in dynamic environments. 展开更多
关键词 Genetic algorithms random immigrants elitism-based immigrants dualism dynamic optimization problems.
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An improved genetic algorithm with dynamic topology 认领 引用 被引量：1
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作者 蔡开泉 唐焱武 +1 位作者 张学军 管祥民 《Chinese Physics B》 SCIE EI CAS CSCD 2016年第12期583-589,共7页
The genetic algorithm （GA） is a nature-inspired evolutionary algorithm to find optima in search space via the interac- tion of individuals. Recently, researchers demonstrated that the interaction topology plays an i... The genetic algorithm （GA） is a nature-inspired evolutionary algorithm to find optima in search space via the interac- tion of individuals. Recently, researchers demonstrated that the interaction topology plays an important role in information exchange among individuals of evolutionary algorithm. In this paper, we investigate the effect of different network topolo- gies adopted to represent the interaction structures. It is found that GA with a high-density topology ends up more likely with an unsatisfactory solution, contrarily, a low-density topology can impede convergence. Consequently, we propose an improved GA with dynamic topology, named DT-GA, in which the topology structure varies dynamically along with the fitness evolution. Several experiments executed with 15 well-known test functions have illustrated that DT-GA outperforms other test GAs for making a balance of convergence speed and optimum quality. Our work may have implications in the combination of complex networks and computational intelligence. 展开更多
关键词 complex networks genetic algorithm dynamic topology
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A Simulation of the Response of a Sounding Temperature Sensor Based on the Combination of a Genetic Algorithm and Computational Fluid Dynamics 认领 引用 被引量：1
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作者 Juanjuan Wang Yajuan Jia Jiangping Nan 《Fluid Dynamics & Materials Processing》 EI 2020年第6期97-111,共15页
The present study aims at improving the accuracy of weather forecast by providing useful information on the behavior and response of a sounding temperature sensor.A hybrid approach relying on Computational Fluid Dynam... The present study aims at improving the accuracy of weather forecast by providing useful information on the behavior and response of a sounding temperature sensor.A hybrid approach relying on Computational Fluid Dynamics and a genetic algorithm(GA)is used to simulate the system represented by the bead thermistor and the surrounding air.In particular,the influence of different lead angles,sensor lead length,and lead number is considered.The results have shown that when the length of the lead wire of the bead thermistor is increased,the radiation temperature rise is reduced;when the number of lead wire is four and the angle between the lead wires is 180°,the solar radiation angle has a scarce influence on the radiation temperature rise of the sounding temperature sensor. 展开更多
关键词 Sounding temperature sensor genetic algorithm radiation temperature rise computational fluid dynamics bead thermistor
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Hydraulic Self Servo Swing Cylinder Structure Optimization and Dynamic Characteristics Analysis Based on Genetic Algorithm 认领 引用 被引量：1
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作者 Lin Jiang Ruolin Wu Zhichao Zhu 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2015年第4期36-46,共11页
The dynamic characteristics of hydraulic self servo swing cylinder were analyzed according to the hydraulic system natural frequency formula. Based on that,a method of the hydraulic self servo swing cylinder structure... The dynamic characteristics of hydraulic self servo swing cylinder were analyzed according to the hydraulic system natural frequency formula. Based on that,a method of the hydraulic self servo swing cylinder structure optimization based on genetic algorithm was proposed in this paper. By analyzing the four parameters that affect the dynamic characteristics, we had to optimize the structure to obtain as larger the Dm( displacement) as possible under the condition with the purpose of improving the dynamic characteristics of hydraulic self servo swing cylinder. So three state equations were established in this paper. The paper analyzed the effect of the four parameters in hydraulic self servo swing cylinder natural frequency equation and used the genetic algorithm to obtain the optimal solution of structure parameters. The model was simulated by substituting the parameters and initial value to the simulink model. Simulation results show that: using self servo hydraulic swing cylinder natural frequency equation to study its dynamic response characteristics is very effective.Compared with no optimization,the overall system dynamic response speed is significantly improved. 展开更多
关键词 hydraulic self servo swing cylinder genetic algorithm natural frequency structural optimization dynamic characteristic
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Dynamic inversion of the rupture parameters on fault system with complex geometry:A GPU parallel genetic algorithm based on BIEM 认领 引用
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作者 Feng Qian Haiming Zhang 《Earthquake Science》 2019年第5期187-196,共10页
In this study,we attempted to perform an earthquake source dynamic inversion to obtain dynamic parameters on fault system with complex geometry.The forward modeling of the spontaneous rupture process is carried out us... In this study,we attempted to perform an earthquake source dynamic inversion to obtain dynamic parameters on fault system with complex geometry.The forward modeling of the spontaneous rupture process is carried out using a boundary integral equation method(BIEM)based on unstructured meshing,and the inversion method is implemented by a genetic algorithm based on a parallel acceleration of the GPU.The source model in this study is a branched fault,which is described by two physical parameters,the initial stress T0 and the critical slip-weakening distance Dc.We investigated the effect of the inherited parameters on the accuracy and convergence of the inversion simulation.Numerical results showed that if a set of parameters are assigned properly,the inversion of rupture parameters is accurate and converges fast.It is easy to converge to a local optimal solution during the inversion process if inappropriate inherited parameters are selected.Compared with T0,D。has better convergence and accuracy in.the inversion process. 展开更多
关键词 dynamic inversion genetic algorithm initial stress critical slip-weakening distance
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A genetic algorithm for dynamic parameters reverse deduction of integrated anchorage system 认领 引用
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作者 张永兴 《Journal of Chongqing University》 2006年第1期46-49,共4页
In the analysis of the system of anchoring bar and wall rock in small strain and longitudinal vibration dynamic response, the influence of the cement grouting as well as the rock layer on the anchor bar can be evaluat... In the analysis of the system of anchoring bar and wall rock in small strain and longitudinal vibration dynamic response, the influence of the cement grouting as well as the rock layer on the anchor bar can be evaluated as the two kinds of parameters: the dynamic stiffness and the damp, which are the vital reference of the anchorage quality. Based on the analytic solution to the dynamic equation of the integrated anchor bar, the new approach which combines genetic algorithm and the toolbox of Matlab is applied to solve the problem of multi-parameters reverse deduction for integrated anchorage system in dynamic testing. Using the traits of the self-organizing, self-adapting and the fast convergence speed of the genetic algorithm, the optimum of all possible solutions to dynamic parameters is obtained by calculating the project instances. Examples show that the method presented in this paper is effective and reliable. 展开更多
关键词 integrated anchorage dynamic parameters reverse deduction genetic algorithm
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Comparison between dynamic programming and genetic algorithm for hydro unit economic load dispatch 认领 引用 被引量：1
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作者 Bin XU Ping-an ZHONG +2 位作者 Yun-fa ZHAO Yu-zuo ZHU Gao-qi ZHANG 《Water Science and Engineering》 EI CAS CSCD 2014年第4期420-432,共13页
The hydro unit economic load dispatch （ELD） is of great importance in energy conservation and emission reduction. Dynamic programming （DP） and genetic algorithm （GA） are two representative algorithms for solving... The hydro unit economic load dispatch （ELD） is of great importance in energy conservation and emission reduction. Dynamic programming （DP） and genetic algorithm （GA） are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA＇s performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases. 展开更多
关键词 hydro unit economic load dispatch dynamic programming genetic algorithm numerical experiment
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Dynamic airspace sectorization via improved genetic algorithm 认领 引用 被引量：9
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作者 Yangzhou Chen Hong Bi +1 位作者 Defu Zhang Zhuoxi Song 《Journal of Modern Transportation》 2013年第2期117-124,共8页
This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is ... This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic. 展开更多
关键词 Dynamic airspace sectorization （DAS） Improved genetic algorithm （iGA） Graph model Multiple populations Hybrid coding Sector constraints
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Computational Fluid Dynamics Based Bulbous Bow Optimization Using a Genetic Algorithm 认领 引用 被引量：6
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作者 Shahid Mahmood Debo Huang 《Journal of Marine Science and Application》 2012年第3期286-294,共9页
Computational fluid dynamics （CFD） plays a major role in predicting the flow behavior of a ship. With the development of fast computers and robust CFD software, CFD has become an important tool for designers and eng... Computational fluid dynamics （CFD） plays a major role in predicting the flow behavior of a ship. With the development of fast computers and robust CFD software, CFD has become an important tool for designers and engineers in the ship industry. In this paper, the hull form of a ship was optimized for total resistance using CFD as a calculation tool and a genetic algorithm as an optimization tool. CFD based optimization consists of major steps involving automatic generation of geometry based on design parameters, automatic generation of mesh, automatic analysis of fluid flow to calculate the required objective/cost function, and finally an optimization tool to evaluate the cost for optimization. In this paper, integration of a genetic algorithm program, written in MATLAB, was carried out with the geometry and meshing software GAMBIT and CFD analysis software FLUENT. Different geometries of additive bulbous bow were incorporated in the original hull based on design parameters. These design variables were optimized to achieve a minimum cost function of ＂total resistance＂. Integration of a genetic algorithm with CFD tools proves to be effective for hull form ootimization. 展开更多
关键词 bulbous bow genetic algorithm computational fluid dynamics （CFD） total resistance
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Dynamic alliance target tracking based on genetic algorithms in wireless sensor networks 认领 引用
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作者 Zhang Shi Zhang Zhe Zhu Jichang 《China Communications》 SCIE 2007年第4期55-60,共6页
Dynamic alliance(DA),namely,virtual corporations (VCs),is an enterprise management method. It means a temporary union formed by some independent commercial processes or corporations.Here, genetic algorithms(GA) is app... Dynamic alliance(DA),namely,virtual corporations (VCs),is an enterprise management method. It means a temporary union formed by some independent commercial processes or corporations.Here, genetic algorithms(GA) is applied to the research of nodes DA selection optimization in wireless sensor networks(WSN) target tracking(TT) problem.The detailed optimized selection method is presented in the paper and a typical simulation is conducted to verify the effectiveness of our model. 展开更多
关键词 dynamic alliance wireless sensor networks genetic algorithms target tracking
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Unrelated Parallel-Machine Scheduling Problem with Time-Changing Effects and Dynamic Job Arrivals 认领 引用
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作者 GUAN Zhicheng ZHANG Xinying CHEN Lu 《Journal of Shanghai Jiaotong university(Science)》 EI 2026年第4期1057-1070,I0022,共14页
With machine deterioration,time-changing effects are observed in the ion implantation work center of wafer fabrication.Furthermore,jobs arrive in a dynamic pattern.A mixed integer stochastic programming model is formu... With machine deterioration,time-changing effects are observed in the ion implantation work center of wafer fabrication.Furthermore,jobs arrive in a dynamic pattern.A mixed integer stochastic programming model is formulated to address the unrelated parallel-machine scheduling problem at the work center.The objective is to minimize the average flow time of wafers.Time-changing effects and dynamic job arrivals are considered simultaneously.A genetic algorithm with a reinforcement learning procedure(GA-RL)is developed to solve real-size problems.The reinforcement learning procedure aims to determine the optimal confidence levels during the search for the best solution.Computational analyses demonstrate the efficiency of the GA-RL.Sensitivity analyses provide valuable managerial insights into actual production processes. 展开更多
关键词 dynamic job arrivals parallel-machine scheduling time-changing effects genetic algorithm reinforcement learning
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Solving Dynamic Spectrum Management Problem Based on Cloud Computing Using Genetic Algorithm 认领 引用
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作者 Ping-Liang Chen Yu-Cheng Lin Shin-Jia Chen 《Journal of Electronic Science and Technology》 CAS 2013年第2期132-139,共8页
With the rapid development of wireless sensor network （WSN）, the demands of limited radio frequency spectrum rise sharply, thereby dealing with the frequency assignment of WSN scientifically and efficiently becomes ... With the rapid development of wireless sensor network （WSN）, the demands of limited radio frequency spectrum rise sharply, thereby dealing with the frequency assignment of WSN scientifically and efficiently becomes a popular topic. To improve the frequency utilization rate in WSN, a spectrum management system for WSN combined with cloud computing technology should be considered. From the optimization point of view, the study of dynamic spectrum management can be divided into three kinds of methods, including Nash equilibrium, social utility maximization, and competitive economy equilibrium. In this paper, we propose a genetic algorithm based approach to allocate the power spectrum dynamically. The objective is to maximize the sum of individual Shannon utilities with the background interference and crosstalk consideration. Compared to the approach in [1], the experimental result shows better balance between efficiency and effectiveness of our approach. 展开更多
关键词 Terms-Background interference cloudcomputing crosstalk dynamic spectrum management genetic algorithm Shannon utility wireless sensornetwork.
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Hybrid Genetic Algorithm and Variable Neighborhood Search for Dynamic Facility Layout Problem 认领 引用
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作者 Md Sanuwar Uddin 《Open Journal of Optimization》 2015年第4期156-167,共12页
This paper presents a novel hybrid metaheuristic GA-VNS matching genetic algorithm (GA) and variable neighborhood search (VNS) to the dynamic facility layout problem (DFLP). The DFLP is a well-known NP hard problem wh... This paper presents a novel hybrid metaheuristic GA-VNS matching genetic algorithm (GA) and variable neighborhood search (VNS) to the dynamic facility layout problem (DFLP). The DFLP is a well-known NP hard problem which aims at assigning a set of facilities to a set of locations over a time planning horizon so that the total cost including material handling cost and re-arrangement cost is minimized. The proposed hybrid approach in this paper elegantly integrates the exploitation ability of VNS and exploration ability of GA. To examine the performance of the proposed hybrid approach, a set of instance problems have been used from the literature. As demonstrated in the results, the GA-VNS is mighty of attaining high quality solution. Compared with some state-of-the-art algorithms, our proposed hybrid approach is competitive. 展开更多
关键词 Dynamic Facility Layout Genetic Algorithm Material Handling
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Fuzzy Genetic Sharing for Dynamic Optimization 认领 引用
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作者 Khalid Jebari Abdelaziz Bouroumi Aziz Ettouhami 《International Journal of Automation and computing》 2012年第6期616-626,共11页
Recently,genetic algorithms(GAs) have been applied to multi-modal dynamic optimization(MDO).In this kind of optimization,an algorithm is required not only to find the multiple optimal solutions but also to locate a dy... Recently,genetic algorithms(GAs) have been applied to multi-modal dynamic optimization(MDO).In this kind of optimization,an algorithm is required not only to find the multiple optimal solutions but also to locate a dynamically changing optimum.Our fuzzy genetic sharing(FGS) approach is based on a novel genetic algorithm with dynamic niche sharing(GADNS).FGS finds the optimal solutions,while maintaining the diversity of the population.For this,FGS uses several strategies.First,an unsupervised fuzzy clustering method is used to track multiple optima and perform GADNS.Second,a modified tournament selection is used to control selection pressure.Third,a novel mutation with an adaptive mutation rate is used to locate unexplored search areas.The effectiveness of FGS in dynamic environments is demonstrated using the generalized dynamic benchmark generator(GDBG). 展开更多
关键词 Genetic algorithms unsupervised learning fuzzy clustering dynamic optimization evolutionary algorithms dynamic niche sharing Hill s diversity index multi-modal function optimization.
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Hydraulic Optimization of a Double-channel Pump's Impeller Based on Multi-objective Genetic Algorithm 认领 引用 被引量：14
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作者 ZHAO Binjuan WANG Yu +2 位作者 CHEN Huilong QIU Jing HOU Duohua 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2015年第3期634-640,共7页
Computational fluid dynamics（CFD） can give a lot of potentially very useful information for hydraulic optimization design of pumps, however, it cannot directly state what kind of modification should be made to impro... Computational fluid dynamics（CFD） can give a lot of potentially very useful information for hydraulic optimization design of pumps, however, it cannot directly state what kind of modification should be made to improve such hydrodynamic performance. In this paper, a more convenient and effective approach is proposed by combined using of CFD, multi-objective genetic algorithm（MOGA） and artificial neural networks（ANN） for a double-channel pump＇s impeller, with maximum head and efficiency set as optimization objectives, four key geometrical parameters including inlet diameter, outlet diameter, exit width and midline wrap angle chosen as optimization parameters. Firstly, a multi-fidelity fitness assignment system in which fitness of impellers serving as training and comparison samples for ANN is evaluated by CFD, meanwhile fitness of impellers generated by MOGA is evaluated by ANN, is established and dramatically reduces the computational expense. Then, a modified MOGA optimization process, in which selection is performed independently in two sub-populations according to two optimization objectives, crossover and mutation is performed afterword in the merged population, is developed to ensure the global optimal solution to be found. Finally, Pareto optimal frontier is found after 500 steps of iterations, and two optimal design schemes are chosen according to the design requirements. The preliminary and optimal design schemes are compared, and the comparing results show that hydraulic performances of both pumps 1 and 2 are improved, with the head and efficiency of pump 1 increased by 5.7% and 5.2%, respectively in the design working conditions, meanwhile shaft power decreased in all working conditions, the head and efficiency of pump 2 increased by 11.7% and 5.9%, respectively while shaft power increased by 5.5%. Inner flow field analyses also show that the backflow phenomenon significantly diminishes at the entrance of the optimal impellers 1 and 2, both the area of vortex and intensity of vortex decreases in the whole flow channel. This paper provides a promising tool to solve the hydraulic optimization problem of pumps＇ impellers. 展开更多
关键词 double-channel pump＇s impeller multi-objective genetic algorithm artificial neural network computational fluid dynamics（CFD） uni
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Design of S-band photoinjector with high bunch charge and low emittance based on multi-objective genetic algorithm 认领 引用 被引量：7
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作者 Ze-Yi Dai Yuan-Cun Nie +9 位作者 Zi Hui Lan-Xin Liu Zi-Shuo Liu Jian-Hua Zhong Jia-Bao Guan Ji-Ke Wang Yuan Chen Ye Zou Hao-Hu Li Jian-Hua He 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2023年第3期93-105,共13页
High-brightness electron beams are required to drive LINAC-based free-electron lasers(FELs)and storage-ring-based synchrotron radiation light sources.The bunch charge and RMS bunch length at the exit of the LINAC play... High-brightness electron beams are required to drive LINAC-based free-electron lasers(FELs)and storage-ring-based synchrotron radiation light sources.The bunch charge and RMS bunch length at the exit of the LINAC play a crucial role in the peak current;the minimum transverse emittance is mainly determined by the injector of the LINAC.Thus,a photoin-jector with a high bunch charge and low emittance that can simultaneously provide high-quality beams for 4th generation synchrotron radiation sources and FELs is desirable.The design of a 1.6-cell S-band 2998-MHz RF gun and beam dynamics optimization of a relevant beamline are presented in this paper.Beam dynamics simulations were performed by combining ASTRA and the multi-objective genetic algorithm NSGA II.The effects of the laser pulse shape,half-cell length of the RF gun,and RF parameters on the output beam quality were analyzed and compared.The normalized transverse emittance was optimized to be as low as 0.65 and 0.92 mm·mrad when the bunch charge was as high as 1 and 2 nC,respectively.Finally,the beam stability properties of the photoinjector,considering misalignment and RF jitter,were simulated and analyzed. 展开更多
关键词 Electron linear accelerator Photoinjector Beam dynamics Multi-objective genetic algorithm
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A Linear Domain System Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Genetic Algorithm 认领 引用 被引量：13
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作者 Xusheng Lei Yuhu Du 《Journal of Bionic Engineering》 SCIE EI 2010年第2期142-149,共8页
This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft.Byusing the flash memory integrated into the micro guide navigation control module,system records the ... This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft.Byusing the flash memory integrated into the micro guide navigation control module,system records the data sequences of flighttests as inputs(control signals for servos)and outputs(aircraft’s attitude and velocity information).After data preprocessing,thesystem constructs the horizontal and vertical dynamic model for the small unmanned aerial rotorcraft using adaptive geneticalgorithm.The identified model is verified by a series of simulations and tests.Comparison between flight data and the one-stepprediction data obtained from the identification model shows that the dynamic model has a good estimation for real unmannedaerial rotorcraft system.Based on the proposed dynamic model,the small unmanned aerial rotorcraft can perform hovering,turning,and straight flight tasks in real flight tests. 展开更多
关键词 small unmanned aerial rotorcraft dynamic space model model identification adaptive genetic algorithm
FLIGHT DELAY STATE-SPACE MODEL BASED ON GENETIC EM ALGORITHM 认领 引用 被引量：2
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作者 陈海燕 王建东 徐涛 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2011年第3期276-281,共6页
Flight delay prediction remains an important research topic due to dynamic nature in flight operation and numerous delay factors.Dynamic data-driven application system in the control area can provide a solution to thi... Flight delay prediction remains an important research topic due to dynamic nature in flight operation and numerous delay factors.Dynamic data-driven application system in the control area can provide a solution to this problem.However,in order to apply the approach,a state-space flight delay model needs to be established to represent the relationship among system states,as well as the relationship between system states and input/output variables.Based on the analysis of delay event sequence in a single flight,a state-space mixture model is established and input variables in the model are studied.Case study is also carried out on historical flight delay data.In addition,the genetic expectation-maximization（EM）algorithm is used to obtain the global optimal estimates of parameters in the mixture model,and results fit the historical data.At last,the model is validated in Kolmogorov-Smirnov tests.Results show that the model has reasonable goodness of fitting the data,and the search performance of traditional EM algorithm can be improved by using the genetic algorithm. 展开更多
关键词 flight delay predictions dynamic data-driven application system genetic EM algorithm
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A Comparative Study on Hydrodynamic Optimization Approaches for AUV Design Using CFD 认领 引用
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作者 KL Vasudev Manish Pandey Jaan H.Pu 《Fluid Dynamics & Materials Processing》 EI 2025年第7期1545-1569,共25页
This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully i... This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully integrated optimisation framework is developed accordingly,combining a single-objective Genetic Algorithm(GA)for design parameter generation,Computer-Aided Geometric Design(CAGD)for the creation of hull geometries and associated fluid domains,and a Reynolds-Averaged Navier-Stokes(RANS)solver for evaluating hydrodynamic performance metrics.This unified approach eliminates manual intervention,enabling automated determination of optimal hull configurations.Three distinct optimisation problems are addressed using the proposed methodology.First,the drag minimisation of a reference afterbody geometry(A1)at zero angle of attack is performed under constraints of fixed length and internal volume for various flow velocities spanning the range from 0.5 to 15 m/s.Second,the lift-to-drag ratio of A1 is maximised at a 6°angle of attack,maintaining constant total length and internal volume.Third,delivered power is minimised for A1 at a 0°angle of attack.The comparative analysis of results from all three optimisation cases reveals hull shapes with practical design significance.Notably,the shape optimised for minimum delivered power outperforms the other two across a range of velocities.Specifically,it achieves reductions in required power by 7.6%,7.8%,10.2%,and 13.04%at velocities of 0.5,1.0,1.5,and 2.152 m/s,respectively. 展开更多
关键词 Lift-to-drag ratio delivered power hydrodynamic drag autonomous underwater vehicle/glider(AUV/G) genetic algorithm(GA) computational fluid dynamics(CFD)
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