An evolutionary computational approach to probabilistic neural network with application to hepatic cancer diagnosis

F. Gorunescu, Marina Gorunescu, E. El-Darzi, S. Gorunescu
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引用次数: 16

Abstract

The performance of a probabilistic neural network is strongly influenced by the smoothing parameter. This paper introduces an evolutionary approach based on genetic algorithm to optimise the search of the smoothing parameter in a modified probabilistic neural network. A Java implementation is introduced and the computational results showed the viability of this hybrid approach to determine the optimum diagnosis for hepatic diseases.
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概率神经网络的进化计算方法及其在肝癌诊断中的应用
概率神经网络的性能受平滑参数的影响很大。本文介绍了一种基于遗传算法的进化方法来优化改进概率神经网络中平滑参数的搜索。介绍了一个Java实现,计算结果表明,这种混合方法在确定肝脏疾病的最佳诊断方面是可行的。
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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