期刊文献+

二次检索

题名
关键词
文摘
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1,056篇文章
< 1 2 53 >
每页显示 20 50 100
Manipulator Neural Network Control Based on Fuzzy Genetic Algorithm 被引量:1
1
作者 崔平远 Yang Guojun 《High Technology Letters》 EI CAS 2001年第1期63-66,共4页
The three-layer forward neural networks are used to establish the inverse kinematics models of robot manipulators. The fuzzy genetic algorithm based on the linear scaling of the fitness value is presented to update th... The three-layer forward neural networks are used to establish the inverse kinematics models of robot manipulators. The fuzzy genetic algorithm based on the linear scaling of the fitness value is presented to update the weights of neural networks. To increase the search speed of the algorithm, the crossover probability and the mutation probability are adjusted through fuzzy control and the fitness is modified by the linear scaling method in FGA. Simulations show that the proposed method improves considerably the precision of the inverse kinematics solutions for robot manipulators and guarantees a rapid global convergence and overcomes the drawbacks of SGA and the BP algorithm. 展开更多
关键词 Inverse kinematics neural networks fuzzy control genetic algorithm Fitness function
下载PDF
Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria
2
作者 Djeldjli Halima Benatiallah Djelloul +3 位作者 Ghasri Mehdi Tanougast Camel Benatiallah Ali Benabdelkrim Bouchra 《Computers, Materials & Continua》 SCIE EI 2024年第6期4725-4740,共16页
When designing solar systems and assessing the effectiveness of their many uses,estimating sun irradiance is a crucial first step.This study examined three approaches(ANN,GA-ANN,and ANFIS)for estimating daily global s... When designing solar systems and assessing the effectiveness of their many uses,estimating sun irradiance is a crucial first step.This study examined three approaches(ANN,GA-ANN,and ANFIS)for estimating daily global solar radiation(GSR)in the south of Algeria:Adrar,Ouargla,and Bechar.The proposed hybrid GA-ANN model,based on genetic algorithm-based optimization,was developed to improve the ANN model.The GA-ANN and ANFIS models performed better than the standalone ANN-based model,with GA-ANN being better suited for forecasting in all sites,and it performed the best with the best values in the testing phase of Coefficient of Determination(R=0.9005),Mean Absolute Percentage Error(MAPE=8.40%),and Relative Root Mean Square Error(rRMSE=12.56%).Nevertheless,the ANFIS model outperformed the GA-ANN model in forecasting daily GSR,with the best values of indicators when testing the model being R=0.9374,MAPE=7.78%,and rRMSE=10.54%.Generally,we may conclude that the initial ANN stand-alone model performance when forecasting solar radiation has been improved,and the results obtained after injecting the genetic algorithm into the ANN to optimize its weights were satisfactory.The model can be used to forecast daily GSR in dry climates and other climates and may also be helpful in selecting solar energy system installations and sizes. 展开更多
关键词 Solar energy systems genetic algorithm neural networks hybrid adaptive neuro fuzzy inference system solar radiation
下载PDF
Application of hybrid coded genetic algorithm in fuzzy neural network controller
3
作者 杨振强 杨智民 +2 位作者 王常虹 庄显义 宁慧 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2000年第1期65-68,共4页
Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during... Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during the crossover operation and decimal encoding during the mutation operation, and the way of accepting new individuals by probability adopted, by which a new individual is accepted and its parent is discarded when its fitness is higher than that of its parent, and a new individual is accepted by probability when its fitness is lower than that of its parent. And concludes with calculations made with an example that these improvements enhance the speed of genetic algorithms to optimize the fuzzy neural network controller. 展开更多
关键词 genetic algorithm fuzzy neural network COST function HYBRID CODING
下载PDF
NEURAL NETWORK PREDICTIVE CONTROL WITH HIERARCHICAL GENETIC ALGORITHM
4
作者 刘宝坤 王慧 李光泉 《Transactions of Tianjin University》 EI CAS 1998年第2期48-50,共3页
A kind of predictive control based on the neural network(NN) for nonlinear systems with time delay is addressed.The off line NN model is obtained by using hierarchical genetic algorithms (HGA) to train a sequence da... A kind of predictive control based on the neural network(NN) for nonlinear systems with time delay is addressed.The off line NN model is obtained by using hierarchical genetic algorithms (HGA) to train a sequence data of input and output.Output predictions are obtained by recursively mapping the NN model.The error rectification term is introduced into a performance function that is directly optimized while on line control so that it overcomes influences of the mismatched model and disturbances,etc.Simulations show the system has good dynamic responses and robustness. 展开更多
关键词 neural networks(NN) predictive control hierarchical genetic algorithms nonlinear system
下载PDF
Intelligent vehicle lateral controller design based on genetic algorithmand T-S fuzzy-neural network
5
作者 RuanJiuhong FuMengyin LiYibin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2005年第2期382-387,共6页
Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be reg... Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem. 展开更多
关键词 intelligent vehicle genetic algorithm fuzzy-neural network lateral control robustness.
下载PDF
Design of Robotic Visual Servo Control Based on Neural Network and Genetic Algorithm 被引量:9
6
作者 Hong-Bin Wang Mian Liu 《International Journal of Automation and computing》 EI 2012年第1期24-29,共6页
A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without req... A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control. 展开更多
关键词 Visual servo image Jacobian back propagation (BP) neural network genetic algorithm robot control
下载PDF
Fuzzy Control System of Hydraulic Roll Bending Based on Genetic Neural Network 被引量:2
7
作者 JIAChun-yu LIUHong-min ZHOUHui-feng 《Journal of Iron and Steel Research International》 SCIE CAS CSCD 2005年第3期22-27,共6页
For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system ... For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system has settled the problems of recognizing and controlling the unknown, uncertain and nonlinear system successfully, and has been applied to hydraulic roll bending control. The simulation results indicate that the system has good performance and strong robustness, and is better than traditional PID and neural-fuzzy control. The method is an effective tool to control roll bending force with increased dynamic response speed of control system and enhanced tracking accuracy. 展开更多
关键词 genetic algorithm neural network fuzzy control hydraulic roll bending SHAPE
下载PDF
Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm 被引量:1
8
作者 沈虹 万健如 +2 位作者 张志超 刘英培 李光叶 《Transactions of Tianjin University》 EI CAS 2009年第4期245-248,共4页
Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic alg... Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic algorithm is used to search the weight of the neural network. At the same time, the multi-objective-based evaluation function is adopted, in which there are three main indicators including the passenger waiting time, car passengers number and the number of stops. Different weights are given to meet the actual needs. The optimal values of the evaluation function are obtained, and the optimal dispatch control of the elevator group control system based on neural network is realized. By analyzing the running of the elevator group control system, all the processes and steps are presented. The validity of the hybrid algorithm is verified by the dynamic imitation performance. 展开更多
关键词 elevator group control genetic algorithm neural network hybrid algorithm
下载PDF
Parameters Optimization of the Heating Furnace Control Systems Based on BP Neural Network Improved by Genetic Algorithm 被引量:4
9
作者 Qiong Wang Xiaokan Wang 《Journal on Internet of Things》 2020年第2期75-80,共6页
The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model,because the heating furnace for heating treatment with the big inertia,the ... The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model,because the heating furnace for heating treatment with the big inertia,the pure time delay and nonlinear time-varying.Proposed one kind optimized variable method of PID controller based on the genetic algorithm with improved BP network that better realized the completely automatic intelligent control of the entire thermal process than the classics critical purporting(Z-N)method.A heating furnace for the object was simulated with MATLAB,simulation results show that the control system has the quicker response characteristic,the better dynamic characteristic and the quite stronger robustness,which has some promotional value for the control of industrial furnace. 展开更多
关键词 genetic algorithm parameter optimization PID control BP neural network heating furnace
下载PDF
Fuzzy Optimization of an Elevator Mechanism Applying the Genetic Algorithm and Neural Networks 被引量:2
10
作者 XI Ping-yuan WANG Bing +1 位作者 SHENTU Liu-fang HU Heng-yin 《International Journal of Plant Engineering and Management》 2005年第4期236-240,共5页
Considering the indefinite character of the value of design parameters and being satisfied with load-bearing capacity and stiffness, the fuzzy optimization mathematical model is set up to minimize the volume of tooth ... Considering the indefinite character of the value of design parameters and being satisfied with load-bearing capacity and stiffness, the fuzzy optimization mathematical model is set up to minimize the volume of tooth corona of a worm gear in an elevator mechanism. The method of second-class comprehensive evaluation was used based on the optimal level cut set, thus the optimal level value of every fuzzy constraint can be attained; the fuzzy optimization is transformed into the usual optimization. The Fast Back Propagation of the neural networks algorithm are adopted to train feed-forward networks so as to fit a relative coefficient. Then the fitness function with penalty terms is built by a penalty strategy, a neural networks program is recalled, and solver functions of the Genetic Algorithm Toolbox of Matlab software are adopted to solve the optimization model. 展开更多
关键词 elevator mechanism fuzzy design optimization genetic algorithm and neural networks toolbox
下载PDF
Development of an electrode intelligent design system based on adaptive fuzzy neural network and genetic algorithm
11
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
下载PDF
Applying Neural Network withGenetic Algorithm and FuzzySelection Models to Select Equipmentsfor Fully-Mechanized Coal Mining
12
作者 王新宇 吴瑞明 冯春花 《Journal of China University of Mining and Technology》 2004年第2期147-151,共5页
According to the typical engineering samples, a neural net work model with genetic algorithm to optimize weight values is put forward to forecast the productivities and efficiencies of mining faces. By this model we c... According to the typical engineering samples, a neural net work model with genetic algorithm to optimize weight values is put forward to forecast the productivities and efficiencies of mining faces. By this model we can obtain the possible achievements of available equipment combinations under certain geological situations of fully-mechanized coal mining faces. Then theory of fuzzy selection is applied to evaluate the performance of each equipment combination. By detailed empirical analysis, this model integrates the functions of forecasting mining faces' achievements and selecting optimal equipment combination and is helpful to the decision of equipment combination for fully-mechanized coal mining. 展开更多
关键词 genetic algorithm artificial neural network fuzzy SELECTION SELECTION of equipment combination
下载PDF
Dynamic Bandwidth Allocation Technique in ATM Networks Based on Fuzzy Neural Networks and Genetic Algorithm
13
作者 Zhang Liangjie Li Yanda Wang Pu (Dept of Automation Tsinghua University, Beijing 100084) 《通信学报》 EI CSCD 北大核心 1997年第3期10-17,共8页
DynamicBandwidthAlocationTechniqueinATMNetworksBasedonFuzyNeuralNetworksandGeneticAlgorithm①ZhangLiangjieLiY... DynamicBandwidthAlocationTechniqueinATMNetworksBasedonFuzyNeuralNetworksandGeneticAlgorithm①ZhangLiangjieLiYandaWangPu(Deptof... 展开更多
关键词 模糊神经网 动态带宽分配 异步传输网 基因算法
下载PDF
A Short-Term Traffic Flow Prediction ModelBased on Quantum Genetic Algorithm andFuzzy RBF Neural Networks
14
作者 Kun Zhang 《计算机科学与技术汇刊(中英文版)》 2016年第1期24-39,共16页
关键词 神经网络 流动模拟 基因算法 RBF 交通 预言 短期 ARIMA
下载PDF
Adaptive control of parallel manipulators via fuzzy-neural network algorithm 被引量:3
15
作者 Dachang ZHU Yuefa FANG 《控制理论与应用(英文版)》 EI 2007年第3期295-300,共6页
This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms (FNNA). With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric u... This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms (FNNA). With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme, we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom (DoF). The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF. 展开更多
关键词 Parallel manipulator Adaptive control fuzzy neural network algorithm SIMULATION
下载PDF
An Integrated Use of Advanced T2 Statistics and Neural Network and Genetic Algorithm in Monitoring Process Disturbance 被引量:1
16
作者 Xiuhong WANG 《Journal of Software Engineering and Applications》 2009年第5期335-343,共9页
Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of O... Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of Opportunity” and autocorrelation. In this paper, advanced T2 statistics model and neural networks scheme are combined to solve the above problems: use T2 statistics technique to solve the problem of autocorrelation;adopt neural networks technique to solve the problem of “Window of Opportunity” and identification of disturbance causes. At the same time, regarding the shortcoming of neural network technique that its algorithm has a low speed of convergence and it is usually plunged into local optimum easily. Genetic algorithm was proposed to train samples in this paper. Results of the simulation ex-periments show that this method can detect the process disturbance quickly and accurately as well as identify the dis-turbance type. 展开更多
关键词 T2 STATISTICS neural networks Statistical PROCESS control Engineering PROCESS control genetic algorithm
下载PDF
Research on Financial Distress Prediction with Adaptive Genetic Fuzzy Neural Networks on Listed Corporations of China
17
作者 Zhibin XIONG 《International Journal of Communications, Network and System Sciences》 2009年第5期385-391,共7页
To design a multi-population adaptive genetic BP algorithm, crossover probability and mutation probability are self-adjusted according to the standard deviation of population fitness in this paper. Then a hybrid model... To design a multi-population adaptive genetic BP algorithm, crossover probability and mutation probability are self-adjusted according to the standard deviation of population fitness in this paper. Then a hybrid model combining Fuzzy Neural Network and multi-population adaptive genetic BP algorithm—Adaptive Genetic Fuzzy Neural Network (AGFNN) is proposed to overcome Neural Network’s drawbacks. Furthermore, the new model has been applied to financial distress prediction and the effectiveness of the proposed model is performed on the data collected from a set of Chinese listed corporations using cross validation approach. A comparative result indicates that the performance of AGFNN model is much better than the ones of other neural network models. 展开更多
关键词 MULTI-POPULATION ADAPTIVE genetic BP algorithm fuzzy neural network Cross Validation FINANCIAL DISTRESS
下载PDF
HPSO-based fuzzy neural network control for AUV 被引量:1
18
作者 Lei ZHANG Yongjie PANG Yumin SU Yannan LIANG 《控制理论与应用(英文版)》 EI 2008年第3期322-326,共5页
A fuzzy neural network controller for underwater vehicles has many parameters difficult to tune manually. To reduce the numerous work and subjective uncertainties in manual adjustments, a hybrid particle swarm optimiz... A fuzzy neural network controller for underwater vehicles has many parameters difficult to tune manually. To reduce the numerous work and subjective uncertainties in manual adjustments, a hybrid particle swarm optimization (HPSO) algorithm based on immune theory and nonlinear decreasing inertia weight (NDIW) strategy is proposed. Owing to the restraint factor and NDIW strategy, an HPSO algorithm can effectively prevent premature convergence and keep balance between global and local searching abilities. Meanwhile, the algorithm maintains the ability of handling multimodal and multidimensional problems. The HPSO algorithm has the fastest convergence velocity and finds the best solutions compared to GA, IGA, and basic PSO algorithm in simulation experiments. Experimental results on the AUV simulation platform show that HPSO-based controllers perform well and have strong abilities against current disturbance. It can thus be concluded that the proposed algorithm is feasible for application to AUVs. 展开更多
关键词 Autonomous underwater vehicle fuzzy neural network Model reference adaptive control Particle swarm optimization algorithm Immune theory
下载PDF
Nonlinear model predictive control based on support vector machine and genetic algorithm 被引量:5
19
作者 冯凯 卢建刚 陈金水 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期2048-2052,共5页
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ... This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection. 展开更多
关键词 Support vector machine genetic algorithm Nonlinear model predictive control neural network Modeling
下载PDF
Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis 被引量:3
20
作者 LIU Bo WANG Yong WANG Hong-jian 《哈尔滨工程大学学报》 EI CAS CSCD 北大核心 2006年第B07期547-551,共5页
关键词 聚类分析 遗传算法 模糊自适应谐振理论 人工神经网络
下载PDF
上一页 1 2 53 下一页 到第
使用帮助 返回顶部