Description: 为了更好了解遗传神经网络在系统中的对比效果，我们以室内温度控制为例，设室内的温度控制目标为18℃（20℃），其他参数保持不变的情况下，分别按照单独神经网络和基于遗传算法优化后的神经网络控制进行仿真实验.仿真结果表明，上述应用遗传算法优化的神经网络是非常有效的，通过运用遗传算法对神经网络进行优化，使其具有良好的泛化能力和快速的收敛性。-To better understand the genetic neural network contrast in the system, we control the indoor temperature, for example, set the room temperature control goal is 18 ℃ (20 ℃), other parameters remaining unchanged, respectively, according to a separate neural networks optimized based on genetic algorithm and neural network control simulation. The simulation results show that the genetic algorithm to optimize the neural network is very effective, through the use of genetic algorithms to optimize the neural network, it has a good generalization ability and fast convergence. Platform: |
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Author: |
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Description: 基于遗传算法的人工生命模拟，来个例子，大家好理解-Artificial life based on genetic algorithm simulation to an example, Hello everybody understand Platform: |
Size: 7168 |
Author:周科 |
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Description: 遗传算法在连锁网点选址模拟中的应用，供大家参考。本程序对研究遗传算法应用的各位很有用-Location of outlets in the chain of genetic algorithm simulation applications, for your reference. The genetic algorithm program to study the application you are useful Platform: |
Size: 7168 |
Author:李望 |
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Description: 用C++编程后遗传算法的仿真实验，非常有用，大家可以下载来运行看看结果。-C++ programmed genetic algorithm simulation, very useful, you can download to run look at the result. Platform: |
Size: 689152 |
Author:努力 |
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Description: tinyos 蚁群算法(ant colony optimization, ACO)，又称蚂蚁算法，是一种用来在图中寻找优化路径的机率型算法。它由Marco Dorigo于1992年在他的博士论文中提出，其灵感来源于蚂蚁在寻找食物过程中发现路径的行为。蚁群算法是一种模拟进化算法,初步的研究表明该算法具有许多优良的性质.针对PID控制器参数优化设计问题,将蚁群算法设计的结果与遗传算法设计的结果进行了比较,数值仿真结果表明,蚁群算法具有一种新的模拟进化优化方法的有效性和应用价值-The tinyos ant colony algorithm (ant colony optimization, ACO), also known as ant algorithm the the probability type algorithm is a method for finding the optimal path in the graph. By Marco Dorigo in his doctoral thesis in 1992, inspired by the behavior of ants found in the process of looking for food path. Ant colony algorithm is a simulated evolutionary algorithm, preliminary studies show that the algorithm has many excellent properties for the PID controller parameters to optimize the design problem, the design of ant colony algorithm and genetic algorithm design compared with numerical simulation results The results show that the ant colony algorithm with a new simulated evolutionary optimization method effectiveness and value Platform: |
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Author:Sofunzhao |
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Description: 涵盖目前识别和智能计算的理论和方法，包括支持向量机，神经网络，决策树，粗糙集理论，模糊集理论，和遗传算法-Covers the recognition and intelligent computing theory and methods, including support vector machines, neural networks, decision trees, rough set theory, fuzzy set theory and genetic algorithm Platform: |
Size: 118784 |
Author:duluxing |
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Description: In this paper, the parameters of PID controller for Automatic
Generation Control (AGC) is tuned according to Generic Algorithms
(GAs) based performance indices in the restructured power systems. The
key idea of the proposed method is to use the fitness function based on
figure of demerit. The simulation results are shown to illustrate
effectiveness of the proposed method to solution of AGC problem under
different operation condition for a wide range of parameter uncertainties
and system nonlinearity Platform: |
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Author:ali |
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Description: matlab仿真说明,文章主要是关于遗传算法求函数最优解问题-matlab simulation shows that article is mainly a function of genetic algorithm for the optimal solution problem Platform: |
Size: 204800 |
Author:fanfan |
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Description: 认知无线电中遗传算法在一定信噪比下的冲突概率仿真实验-The probability of conflict in cognitive radio under certain genetic algorithm simulation SNR Platform: |
Size: 55296 |
Author:刘晨 |
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Description: 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.
Platform: |
Size: 135168 |
Author:samir |
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Description: 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的-Genetic Algorithm (based Algorithm) is a simulation Darwin the evolution natural selection and Genetic mechanism of biological evolution process calculation model, is a kind of searching optimal solution by simulating the natural evolution process of the method, it initially by the university of Michigan J.H olland first proposed in 1975, professor Platform: |
Size: 9767936 |
Author:control lee |
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Description: 遗传算法是计算数学中用于解决最佳化的搜索算法，是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题，一定数量的候选解（称为个体）的抽象表示（称为染色体）的种群向更好的解进化。-Genetic algorithm is used to solve computational mathematics in optimizing search algorithm, an evolutionary algorithm. Evolutionary algorithm was originally borrowed evolutionary biology and developed a number of phenomena, these phenomena, including genetics, mutation, natural selection and hybridization. Genetic algorithms are usually implemented as a way of computer simulation. For an optimization problem, a number of candidate solutions (called individuals) abstract representation of the population (called chromosomes) to better solution evolution. Platform: |
Size: 2048 |
Author:james |
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Description: 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。-Genetic Algorithm (Genetic Algorithm) is a simulation of natural selection and genetics of Darwinian biological evolution computational models of biological evolution, the process is a way to search the optimal solution by simulating the natural evolution. Platform: |
Size: 19456 |
Author:fanshengnan |
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Description: 此為求解最佳化流程之基因演算法，應用mathcad來編寫，mathcad為一簡易好上手之模擬軟體，若只是想跑小系統之初新者，建議使用-This is the process of solving the genetic algorithm to optimize the application mathcad to write, mathcad for a simple simulation software to use it well, if only wanted to run at the beginning of a new small system, it is recommended to use Platform: |
Size: 16384 |
Author:張騰文 |
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Description: 文件包含单纯型算法、复合算法和遗传算法的仿真程序及其结果-File contains the simplex algorithm, complex algorithms and genetic algorithm simulation program and its results Platform: |
Size: 4079616 |
Author:武昊 |
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Search - genetic algorithm simulation