A Novel Methods Based on Clustering Algorithms as The Neural Network Preprocessing

Mariia Martynova, Ondrej Kaas
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Abstract

This paper presents experiments in the preprocessing area for Radial Basic Function Neural Network (RBF NN). The main ideas of it are to find optimal pre-processing methods and algorithms, which can optimize input parameters and expedite the processing of neural network. The proposed methods are some novel experiments with flexible shape parameters and automated determination of the neural network initial parameters.
基于聚类算法的神经网络预处理新方法
本文介绍了径向基函数神经网络(RBF NN)预处理领域的实验。其主要思想是寻找最优的预处理方法和算法,以优化输入参数,加快神经网络的处理速度。提出的方法是一些新颖的实验,具有柔性的形状参数和神经网络初始参数的自动确定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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