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Adaptive Real-Coded Genetic Algorithm for Identifying Motor Systems 认领 引用
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作者 Rong-Fong Fung Chun-Hung Lin 《Modern Mechanical Engineering》 2015年第3期69-86,共18页
In this paper, the main objective is to identify the parameters of motors, which includes a brushless direct current (BLDC) motor and an induction motor. The motor systems are dynamically formulated by the mechanical ... In this paper, the main objective is to identify the parameters of motors, which includes a brushless direct current (BLDC) motor and an induction motor. The motor systems are dynamically formulated by the mechanical and electrical equations. The real-coded genetic algorithm (RGA) is adopted to identify all parameters of motors, and the standard genetic algorithm (SRGA) and various adaptive genetic algorithm (ARGAs) are compared in the rotational angular speeds and fitness values, which are the inverse of square differences of angular speeds. From numerical simulations and experimental results, it is found that the SRGA and ARGA are feasible, the ARGA can effectively solve the problems with slow convergent speed and premature phenomenon, and is more accurate in identifying system’s parameters than the SRGA. From the comparisons of the ARGAs in identifying parameters of motors, the best ARGA method is obtained and could be applied to any other mechatronic systems. 展开更多
关键词 Adaptive Real-Coded Genetic Algorithm (ARGA) Brushless Direct Current Motor (BLDC) Electrical Fan Induction Motor System Identification
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Inverse procedure for determining model parameter of soils using real-coded genetic algorithm 认领 引用 被引量：11
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作者 李守巨 邵龙潭 +1 位作者 王吉喆 刘迎曦 《Journal of Central South University》 SCIE EI CAS 2012年第6期1764-1770,共7页
The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of... The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated. 展开更多
关键词 parameter estimation real-coded genetic algorithm tri-dimensional compression test gradient-based optimization
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Adaptive genetic algorithm with the criterion of premature convergence 认领 引用 被引量：18
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作者 袁晓辉 曹玲 夏良正 《Journal of Southeast University(English Edition)》 EI CAS 2003年第1期40-43,共4页
To counter the defect of traditional genetic algorithms, an improved adaptivegenetic algorithm with the criterion of premature convergence is provided. The occurrence ofpremature convergence is forecasted using colony... To counter the defect of traditional genetic algorithms, an improved adaptivegenetic algorithm with the criterion of premature convergence is provided. The occurrence ofpremature convergence is forecasted using colony entropy and colony variance. When prematureconvergence occurs, new individuals are generated in proper scale randomly based on superiorindividuals in the colony. We use these new individuals to replace some individuals in the oldcolony. The updated individuals account for 30 percent - 40 percent of all individuals and the sizeof scale is related to the distribution of the extreme value of the target function. Simulationtests show that there is much improvement in the speed of convergence and the probability of globalconvergence. 展开更多
关键词 genetic algorithm premature convergence adaptation
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Fuzzy adaptive genetic algorithm based on auto-regulating fuzzy rules 认领 引用 被引量：10
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作者 喻寿益 邝溯琼 《Journal of Central South University》 SCIE EI CAS 2010年第1期123-128,共6页
There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fi... There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search. 展开更多
关键词 adaptive genetic algorithm fuzzy rules auto-regulating crossover probability adjustment
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Estimation of Kinetic Parameters for Autocatalytic Oxidation of Cyclohexane Based on a Modified Adaptive Genetic Algorithm 认领 引用 被引量：2
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作者 刘平乐 邹丽珊 +2 位作者 罗和安 王良芥 郑金华 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2004年第1期49-54,共6页
A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. Th... A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. The influences of selection strategy, crossover strategy and mutation strategy on algorithm performance are discussed. This algorithm with a specially designed adaptive operator avoids the problem of local optimum usually associated with using standard genetic algorithm and simplex method. The kinetic parameters obtained from the modified genetic algorithm are credible and the calculation results using these parameters agree well with experimental data. Furthermore, a new kinetic model of cyclohexane autocatalytic oxidation is established and the kinetic parameters are estimated by using the modified genetic algorithm. 展开更多
关键词 adaptive genetic algorithm cyclohexane autocatalytic oxidation reaction kinetics
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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
An adaptive genetic algorithm with diversity-guided mutation and its global convergence property 认领 引用 被引量：10
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作者 李枚毅 蔡自兴 孙国荣 《Journal of Central South University of Technology》 2004年第3期323-327,共5页
An adaptive genetic algorithm with diversity-guided mutation, which combines adaptive probabilities of crossover and mutation was proposed. By means of homogeneous finite Markov chains, it is proved that adaptive gene... An adaptive genetic algorithm with diversity-guided mutation, which combines adaptive probabilities of crossover and mutation was proposed. By means of homogeneous finite Markov chains, it is proved that adaptive genetic algorithm with diversity-guided mutation and genetic algorithm with diversity-guided mutation converge to the global optimum if they maintain the best solutions, and the convergence of adaptive genetic algorithms with adaptive probabilities of crossover and mutation was studied. The performances of the above algorithms in optimizing several unimodal and multimodal functions were compared. The results show that for multimodal functions the average convergence generation of the adaptive genetic algorithm with diversity-guided mutation is about 900 less than that of (adaptive) genetic algorithm with adaptive probabilities and genetic algorithm with diversity-guided mutation, and the adaptive genetic algorithm with diversity-guided mutation does not lead to premature convergence. It is also shown that the better balance between overcoming premature convergence and quickening convergence speed can be gotten. 展开更多
关键词 diversity-guided mutation adaptive genetic algorithm Markov chain global convergence
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Adaptive template filter method for image processing based on immune genetic algorithm 认领 引用 被引量：2
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作者 谭冠政 吴建华 +1 位作者 范必双 江斌 《Journal of Central South University》 SCIE EI CAS 2010年第5期1028-1035,共8页
To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventiona... To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments. 展开更多
关键词 image characteristic template match adaptive template filter wavelet transform elitist selection elitist crossover immune genetic algorithm
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An adaptive reanalysis method for genetic algorithm with application to fast truss optimization 认领 引用 被引量：3
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作者 Tao Xu Wenjie Zuo +2 位作者 Tianshuang Xu Guangcai Song Ruichuan Li 《Acta Mechanica Sinica》 SCIE EI CAS 2010年第2期225-234,共10页
Although the genetic algorithm （GA） for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the de... Although the genetic algorithm （GA） for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the design process, the authors present an adaptive reanalysis method for GA and its applications in the optimal design of trusses. This reanalysis technique is primarily derived from the Kirsch＇s combined approximations method. An iteration scheme is adopted to adaptively determine the number of basis vectors at every generation. In order to illustrate this method, three classical examples of optimal truss design are used to validate the proposed reanalysis-based design procedure. The presented numerical results demonstrate that the adaptive reanalysis technique affects very slightly the accuracy of the optimal solutions and does accelerate the design process, especially for large-scale structures. 展开更多
关键词 Truss structure Adaptive reanalysis ·Genetic algorithm ·Fast optimization
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An adaptive genetic algorithm for solving bilevel linear programming problem 认领 引用 被引量：2
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作者 王广民 王先甲 +1 位作者 万仲平 贾世会 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2007年第12期1605-1612,共8页
Bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems. Various methods are proposed for solving this pr... Bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems. Various methods are proposed for solving this problem. Of all the algorithms, the ge- netic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming. In this paper, we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation. In addition, some techniques are adopted not only to deal with the difficulty that most of the chromosomes maybe infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm. The performance of this proposed algorithm is illustrated by the examples from references. 展开更多
关键词 bilevel linear programming genetic algorithm fitness value adaptive operator probabilities crossover and mutation
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Optimal Adaptive Genetic Algorithm Based Hybrid Signcryption Algorithm for Information Security 认领 引用 被引量：1
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作者 R.Sujatha M.Ramakrishnan +1 位作者 N.Duraipandian B.Ramakrishnan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2015年第5期47-68,共22页
The functions of digital signature and public key encryption are simultaneously fulfilled by signcryption,which is a cryptographic primitive.To securely communicate very large messages,the cryptographic primitive call... The functions of digital signature and public key encryption are simultaneously fulfilled by signcryption,which is a cryptographic primitive.To securely communicate very large messages,the cryptographic primitive called signcryption efficiently implements the same and while most of the public key based systems are suitable for small messages,hybrid encryption(KEM-DEM)provides a competent and practical way.In this paper,we develop a hybrid signcryption technique.The hybrid signcryption is based on the KEM and DEM technique.The KEM algorithm utilizes the KDF technique to encapsulate the symmetric key.The DEM algorithm utilizes the Adaptive Genetic Algorithm based Elliptic curve cryptography algorithm to encrypt the original message.Here,for the security purpose,we introduce the three games and we proved the attackers fail to find the security attributes of our proposed signcryption algorithm.The proposed algorithm is analyzed with Daniel of Service(DOS),Brute Force attack and Man In Middle(MIM)attacks to ensure the secure data transaction. 展开更多
关键词 Hybrid Signcryption KEM DEM Adaptive Genetic Algorithm EllipticCurve Cryptography
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ADAPTIVE GENETIC ALGORITHM BASED ON SIX FUZZY LOGIC CONTROLLERS 认领 引用 被引量：3
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作者 朱力立 张焕春 经亚枝 《Transactions of Nanjing University of Aeronautics and Astronautics》 2003年第2期230-235,共6页
The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimiz... The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimization relationship. The use of six fuzzy logic controllers(6FLCs) is proposed for dynamic control genetic operating parameters of a symbolic-coded GA. This paper uses AGA based on 6FLCs to deal with the travelling salesman problem (TSP). Experimental results show that AGA based on 6FLCs is more efficient than a standard GA in solving combinatorial optimization problems similar to TSP. 展开更多
关键词 adaptive genetic algorithm fuzzy controller dynamic parameters control TSP
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Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators 认领 引用 被引量：1
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作者 高胜 赵杰 蔡鹤皋 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2003年第1期72-76,共5页
Adaptive genetic algorithm A SA GA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated ... Adaptive genetic algorithm A SA GA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi robot manipulators. Over the task space of a multi robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi robot to avoid falling into deadlock and calculating of composite C space. Finally, two representative tests are given to validate A SA GA and the strategy of decoupled planning. 展开更多
关键词 multi robot path planning adaptive genetic algorithm simulated annealing decoupled planning
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Alternative Fuzzy Cluster Segmentation of Remote Sensing Images Based on Adaptive Genetic Algorithm 认领 引用 被引量：1
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作者 WANG Jing TANG Jilong +3 位作者 LIU Jibin REN Chunying LIU Xiangnan FENG Jiang 《Chinese Geographical Science》 SCIE 2009年第1期83-88,共6页
Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich textur... Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm(AGA) and Alternative Fuzzy C-Means(AFCM) . Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased,and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means(FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM. 展开更多
关键词 Adaptive Genetic Algorithm （AGA） Alternative Fuzzy C-Means （AFCM） image segmentation remote sensing
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An improved self-calibration approach based on adaptive genetic algorithm for position-based visual servo 认领 引用 被引量：1
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作者 Ding LIU Xiongjun WU Yanxi YANG 《控制理论与应用（英文版）》 2008年第3期246-252,共7页
An improved self-calibrating algorithm for visual servo based on adaptive genetic algorithm is proposed in this paper. Our approach introduces an extension of Mendonca-Cipolla and G. Chesi＇s self-calibration for the ... An improved self-calibrating algorithm for visual servo based on adaptive genetic algorithm is proposed in this paper. Our approach introduces an extension of Mendonca-Cipolla and G. Chesi＇s self-calibration for the positionbased visual servo technique which exploits the singular value property of the essential matrix. Specifically, a suitable dynamic online cost function is generated according to the property of the three singular values. The visual servo process is carried out simultaneous to the dynamic self-calibration, and then the cost function is minimized using the adaptive genetic algorithm instead of the gradient descent method in G. Chesi＇s approach. Moreover, this method overcomes the limitation that the initial parameters must be selected close to the true value, which is not constant in many cases. It is not necessary to know exactly the camera intrinsic parameters when using our approach, instead, coarse coding bounds of the five parameters are enough for the algorithm, which can be done once and for all off-line. Besides, this algorithm does not require knowledge of the 3D model of the object. Simulation experiments are carried out and the results demonstrate that the proposed approach provides a fast convergence speed and robustness against unpredictable perturbations of camera parameters, and it is an effective and efficient visual servo algorithm. 展开更多
关键词 Dynamic self-calibration Visual servo Adaptive genetic algorithm Parameter optimizing Essential matrix Computer vision
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A New Fuzzy Adaptive Genetic Algorithm 认领 引用 被引量：6
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作者 房磊 张焕春 经亚枝 《Journal of Electronic Science and Technology of China》 2005年第1期57-59,71,共3页
Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while kee... Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained. 展开更多
关键词 adaptive genetic algorithm fuzzy logic controller dynamic parameters control population sizes
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Generalized Self-Adaptive Genetic Algorithms 认领 引用 被引量：2
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作者 Bin Wu Xuyan Tu +1 位作者 Jian Wu Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China Department of Information and Control Engineering, Southwest Institute of Technology, Mianyang 621002, China 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS 2000年第1期72-75,共4页
In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenly distributed init... In order to solve the problem between searching performance and convergence of genetic algorithms, a fast genetic algorithm generalized self-adaptive genetic algorithm (GSAGA) is presented. (1) Evenly distributed initial population is generated. (2) Superior individuals are not broken because of crossover and mutation operation for they are sent to subgeneration directly. (3) High quality im- migrants are introduced according to the condition of the population schema. (4) Crossover and mutation are operated on self-adaptation. Therefore, GSAGA solves the coordination problem between convergence and searching performance. In GSAGA, the searching per- formance and global convergence are greatly improved compared with many existing genetic algorithms. Through simulation, the val- idity of this modified genetic algorithm is proved. 展开更多
关键词 generalized self-adaptive genetic algorithm initial population immigration fitness function
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Development of an electrode intelligent design system based on adaptive fuzzy neural network and genetic algorithm 认领 引用
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作者 Huang Jun Xu Yuelan +1 位作者 Wang Luyuan Wang Kehong 《China Welding》 EI CAS 2014年第2期62-66,共5页
The coating on the electrodes contains many kinds of raw materials which affect significantly on the mechanical properties of deposited metals. It is still a problem how to predict and control the mechanical propertie... The coating on the electrodes contains many kinds of raw materials which affect significantly on the mechanical properties of deposited metals. It is still a problem how to predict and control the mechanical properties of deposited metals directly according to the components of coating on the electrodes. In this paper an electrode intelligent design system is developed by means of fuzzy neural network technology and genetic algorithm,, dynamic link library, object linking and embedding and multithreading. The front-end application and customer interface of the system is realized by using visual C ＋＋ program language and taking SQL Server 2000 as background database. It realizes series functions including automatic design of electrode formula, intelligent prediction of electrode properties, inquiry of electrode information, output of process report based on normalized template and electronic storage and search of relative files. 展开更多
关键词 electrode design system adaptive fuzzy neural network genetic algorithm object linking and embedding
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Time-optimal trajectory planning based on improved adaptive genetic algorithm 认领 引用
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作者 孙农亮 王艳君 《Journal of Measurement Science and Instrumentation》 CAS 2012年第2期103-108,共6页
This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined ... This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined with cubic triangular Bezier spline(CTBS).The CTBS based trajectory planning we did before can achieve continuous second and third derivation,hence it meets the stability requirements of the m anipulator.The working time can be greatly reduced by applying IAGA to the puma 560 trajectory planning when considering physical constraints such as angular ve locity,angular acceleration and jerk.Simulation experiments in both Matlab and ADAMS illustrate that TOTP based on IAGA can give a time optimal result with sm oothness and stability. 展开更多
关键词 time-optimal trajectory planning(TOTP) improved adaptive genetic algorithm(IAGA) cubic triangular Bezier spline(CTBS)
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An Adaptive Strategy-incorporated Integer Genetic Algorithm for Wind Farm Layout Optimization 认领 引用 被引量：1
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作者 Tao Zheng Haotian Li +2 位作者 Houtian He Zhenyu Lei Shangce Gao 《Journal of Bionic Engineering》 SCIE EI CSCD 2024年第3期1522-1540,共19页
Energy issues have always been one of the most significant concerns for scientists worldwide.With the ongoing over exploitation and continued outbreaks of wars,traditional energy sources face the threat of depletion.W... Energy issues have always been one of the most significant concerns for scientists worldwide.With the ongoing over exploitation and continued outbreaks of wars,traditional energy sources face the threat of depletion.Wind energy is a readily available and sustainable energy source.Wind farm layout optimization problem,through scientifically arranging wind turbines,significantly enhances the efficiency of harnessing wind energy.Meta-heuristic algorithms have been widely employed in wind farm layout optimization.This paper introduces an Adaptive strategy-incorporated Integer Genetic Algorithm,referred to as AIGA,for optimizing wind farm layout problems.The adaptive strategy dynamically adjusts the placement of wind turbines,leading to a substantial improvement in energy utilization efficiency within the wind farm.In this study,AIGA is tested in four different wind conditions,alongside four other classical algorithms,to assess their energy conversion efficiency within the wind farm.Experimental results demonstrate a notable advantage of AIGA. 展开更多
关键词 Wind farm layout optimization problem Meta-heuristic algorithms Adaptive Integer genetic algorithm
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