Evolutionary Ann Design Using Improved Selection Method

G. Sagar, M. Sathyanarayana
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Abstract

Study Objective: The important issue in Evolutionary Algorithms (EAs), is time-complexity analysis. Here, 1. To consider the concept of take-overtime to obtain the mean hitting time of EA. i.e.  the concept of the takeover time is generalized rather than a selection of operator alone. This generalization is applied to benchmark problems like N-Bit parity. For various input sizes N, the time complexity in terms of number of generations is estimated. To develop an empirical model is also generated for proposed EA using statistical tool. To apply the proper selection method to find the take-overtime.
基于改进选择方法的进化人工神经网络设计
研究目的:时间复杂度分析是进化算法中的一个重要问题。在这里,1。考虑加班的概念来获得ea的平均击中时间,即接管时间的概念是广义的,而不仅仅是操作员的选择。这种泛化应用于像n位奇偶校验这样的基准问题。对于不同的输入大小N,估计了以代数表示的时间复杂度。利用统计工具开发了一个经验模型。采用适当的选择方法来确定加班时间。
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