计算机模拟系统-基于遗传算法的神经网络.doc
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计算机模拟系统-基于遗传算法的神经网络,摘 要小波变换具有时域局部特性和变焦特性，而神经网络具有自学习、自适应、鲁棒性、容错性和推广能力。把两者的优势结合起来形成了小波网络（wavelet neural network, wnn）。小波神经网络是由小波理论支持的一种特殊的前向控制神经网络，兼有小波变换和神经网络两者的优势，是近似计算和预测领域广泛流行的工具。...
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摘 要
小波变换具有时域局部特性和变焦特性，而神经网络具有自学习、自适应、鲁棒性、容错性和推广能力。把两者的优势结合起来形成了小波网络（Wavelet Neural Network, WNN）。小波神经网络是由小波理论支持的一种特殊的前向控制神经网络，兼有小波变换和神经网络两者的优势，是近似计算和预测领域广泛流行的工具。遗传算法和人工神经网络作为两个工具在众多的研究领域得到了广泛的应用，遗传算法和神经网络本身也得到很大发展。遗传算法体现了生物进化中的四个要素，即繁殖、变异、竞争和自然选择。在本篇论文，用遗传算法来构建和训练小波神经网络，以此来近似计算和进行预测。本文提出的遗传算法利用分级染色体对小波神经网络的结构和权值进行编码，遗传算法联合进化规则来构建和训练小波神经网络，同时对网络进行进化。最后用训练后得到的小波神经网络用于函数近似，体现小波神经网络良好的近似功能。
关键词 小波变换 小波神经网络 遗传算法 函数近似
Abstract
Wavelet Neural Network, WNN）The wavelet network has been introduced as a special feed-forward neural network supported by the wavelet theory,and has become a popular tool in the approximation algorithm,which combines the wavelet theory and feed-forward neural netword.. As two kinds of tools , genetic algorithms( GA )and artificial neural network get wide applications in many research areas,and there are many variation in thenselve. Genetic algorithms shows four elements of biologic evolution : propagation , variation , competition and natural selection. In this paper, an evolutionary algorithm is proposed for constructing and training the wavelet network for approximation and forecast. This evolutionary algorithm utilises the hierarchical chromosome to encode the structure and parameters of the wavelet network, and combines a genetic algorithm and evolutionary programming to construct and train the network simultaneously through evolution.In the end, wavelet neural network after being trained is used to approximation of function to performance good approximation of function.
Keywords: Wavelet transforms;Wavelet neural network;Genetic algorithms;Approximation of function
小波变换具有时域局部特性和变焦特性，而神经网络具有自学习、自适应、鲁棒性、容错性和推广能力。把两者的优势结合起来形成了小波网络（Wavelet Neural Network, WNN）。小波神经网络是由小波理论支持的一种特殊的前向控制神经网络，兼有小波变换和神经网络两者的优势，是近似计算和预测领域广泛流行的工具。遗传算法和人工神经网络作为两个工具在众多的研究领域得到了广泛的应用，遗传算法和神经网络本身也得到很大发展。遗传算法体现了生物进化中的四个要素，即繁殖、变异、竞争和自然选择。在本篇论文，用遗传算法来构建和训练小波神经网络，以此来近似计算和进行预测。本文提出的遗传算法利用分级染色体对小波神经网络的结构和权值进行编码，遗传算法联合进化规则来构建和训练小波神经网络，同时对网络进行进化。最后用训练后得到的小波神经网络用于函数近似，体现小波神经网络良好的近似功能。
关键词 小波变换 小波神经网络 遗传算法 函数近似
Abstract
Wavelet Neural Network, WNN）The wavelet network has been introduced as a special feed-forward neural network supported by the wavelet theory,and has become a popular tool in the approximation algorithm,which combines the wavelet theory and feed-forward neural netword.. As two kinds of tools , genetic algorithms( GA )and artificial neural network get wide applications in many research areas,and there are many variation in thenselve. Genetic algorithms shows four elements of biologic evolution : propagation , variation , competition and natural selection. In this paper, an evolutionary algorithm is proposed for constructing and training the wavelet network for approximation and forecast. This evolutionary algorithm utilises the hierarchical chromosome to encode the structure and parameters of the wavelet network, and combines a genetic algorithm and evolutionary programming to construct and train the network simultaneously through evolution.In the end, wavelet neural network after being trained is used to approximation of function to performance good approximation of function.
Keywords: Wavelet transforms;Wavelet neural network;Genetic algorithms;Approximation of function
