Search - genetic algorithm in neural network

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[Software Engineering] Genetic_Algorithms_in_dam_safety_monitoring_neural DL : 0: 本文基于遗传算法思想，采用浮点数矩阵表示编码，在遗传算法的进化过程中加入一定的约束条件等方法，探讨了网络结构的设计和学习。经实例分析，在用于建立大坝安全监控预报模型的前馈神经网络设计中，该方法在满足一定约束条件下，能同时有效地寻找合适的网络结构和相应的参数(神经网络的权值和阈值)，且在精度和速度上都有较大的提高，为实现实时在线分析评价大坝的安全性态提供了有力的技术支持。-Based on the genetic algorithm, using a float matrix coding, Genetic algorithms in the evolutionary process to be bound by certain conditions, to explore the structure of the network design and learning. By analyzing the examples used in the establishment of dam safety monitoring forecasting model of neural network design, The constraint in meeting certain conditions, can effectively find suitable network structure and the corresponding parameters (the neural network weights and thresholds), and the accuracy and speed have improved greatly. To achieve real-time online analysis and evaluation of the safety of the dam states provide strong technical support.
Date : 2008-10-13 Size : 30.33kb User : 汪顺和
[Software Engineering] Genetic_Algorithms_in_dam_safety_monitoring_neural DL : 0: 本文基于遗传算法思想，采用浮点数矩阵表示编码，在遗传算法的进化过程中加入一定的约束条件等方法，探讨了网络结构的设计和学习。经实例分析，在用于建立大坝安全监控预报模型的前馈神经网络设计中，该方法在满足一定约束条件下，能同时有效地寻找合适的网络结构和相应的参数(神经网络的权值和阈值)，且在精度和速度上都有较大的提高，为实现实时在线分析评价大坝的安全性态提供了有力的技术支持。-Based on the genetic algorithm, using a float matrix coding, Genetic algorithms in the evolutionary process to be bound by certain conditions, to explore the structure of the network design and learning. By analyzing the examples used in the establishment of dam safety monitoring forecasting model of neural network design, The constraint in meeting certain conditions, can effectively find suitable network structure and the corresponding parameters (the neural network weights and thresholds), and the accuracy and speed have improved greatly. To achieve real-time online analysis and evaluation of the safety of the dam states provide strong technical support.
Date : 2026-01-03 Size : 30kb User : 汪顺和
[Software Engineering] 1096796061 DL : 0: 用遗传算法该经神经网络在各个领域的应用-The genetic algorithm used by the neural network applications in various fields
Date : 2026-01-03 Size : 1.02mb User : 密码
[Software Engineering] Stereo_match DL : 0: 立体匹配的教程ppt，设计到人工神经网络，遗传算法在立体匹配方面的应用-Stereo matching tutorial PPT, design to the artificial neural network, genetic algorithm is applied in stereo matching
Date : 2026-01-03 Size : 13.25mb User : 杨生远
[Software Engineering] A-hybrid DL : 0: 针对传统的ＢＰ或ＧＡ对模糊神经网络的识别应用存在收敛容易陷入局部极小识别率低下等问题提出一种基于ＢＦＧＳ的混合遗传算法其基本思想为首先构造一种前馈型模糊神经网络结构然后用遗传算法进化若干代后当目标函数的梯度或者范数小于预先设定值则改用ＢＦＧＳ算法进行优化识别仿真实验表明对比ＧＡ该算法收敛速度较快识别精度提高了约７％能够较好地应用于一类模糊神经网络的识别-In traditional BP or GA to identify the application of fuzzy neural network in convergence of easily falling into local minimum problem of low recognition rate is proposed A hybrid genetic algorithm based on BFGS and its basic idea is first to construct a feedforward fuzzy and genetic algorithm is used to evolve neural network structure for several generations When the gradient of the objective function or norm less than the preset value is used to optimize BFGS algorithm recognition experiment compared the algorithm GA The recognition accuracy of fast convergence speed is improved about 7 recognition can be applied to a class of fuzzy neural networks
Date : 2026-01-03 Size : 715kb User : renxiuju
[Software Engineering] CONTROLLER-PARAMETERS-TUNING-USING-GENETIC-ALGORI DL : 0: The paper deals with a controller design for the nonlinear processes using genetic algorithm and neural model. The aim was to improve the control performance using genetic algorithm for optimal PID controller tuning. The plant model has been identified via an artificial neural network from measured data. The genetic algorithm represents an optimisation procedure, where the cost function to be minimized comprises the closed-loop simulation of the control process and a selected performance index evaluation. Using this approach the parameters of the PID controller were optimised in order to become the required behaviour of the control process. Testing of quality control process was realized in simulation environment of Matlab Simulink on selected types of nonlinear dynamic processes.-The paper deals with a controller design for the nonlinear processes using genetic algorithm and neural model. The aim was to improve the control performance using genetic algorithm for optimal PID controller tuning. The plant model has been identified via an artificial neural network from measured data. The genetic algorithm represents an optimisation procedure, where the cost function to be minimized comprises the closed-loop simulation of the control process and a selected performance index evaluation. Using this approach the parameters of the PID controller were optimised in order to become the required behaviour of the control process. Testing of quality control process was realized in simulation environment of Matlab Simulink on selected types of nonlinear dynamic processes.
Date : 2026-01-03 Size : 132kb User : samir
[Software Engineering] feixianxingnihe DL : 0: 在matlab软件中编程实现基于遗传算法优化BP神经网络非线性系统拟合算法-In the matlab software programming based on genetic algorithm to optimize the BP neural network nonlinear system fitting method
Date : 2026-01-03 Size : 47kb User : feiyang_lzk