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AN IMPROVED GENETIC-ALGORITHM-BASED NEURAL-TUNED NEURAL NETWORK

机译:基于改进遗传算法的神经调谐神经网络

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This paper presents a neural-tuned neural network (NTNN), which is trained by an improved genetic algorithm (GA). The NTNN consists of a common neural network and a modified neural network (MNN). In the MNN, a neuron model with two activation functions is introduced. An improved GA is proposed to train the parameters of the proposed network. A set of improved genetic operations are presented, which show superior performance over the traditional GA. The proposed network structure can increase the search space of the network and offer better performance than the traditional feed-forward neural network. Two application examples are given to illustrate the merits of the proposed network and the improved GA.
机译:本文提出了一种神经调谐神经网络(NTNN),该网络由一种改进的遗传算法(GA)进行训练。 NTNN由公共神经网络和改进的神经网络(MNN)组成。在MNN中,引入了具有两个激活函数的神经元模型。提出了一种改进的遗传算法来训练所提出的网络的参数。提出了一组改进的遗传操作,显示出优于传统遗传算法的性能。与传统的前馈神经网络相比,提出的网络结构可以增加网络的搜索空间并提供更好的性能。给出了两个应用实例来说明所提出的网络和改进的遗传算法的优点。

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