基于改进遗传神经网络的图书采购模型分析

Runhua Wang, Yi Tang, Guoquan Liu, Lei Li
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引用次数: 0

摘要

针对目前图书采购过程中缺乏一套科学统一的采购模式和模型的问题,提出了一种基于遗传神经网络的图书采购建模方法。该方法首先对标准遗传算法进行改进,然后将改进后的标准遗传算法作为前馈神经网络训练和前馈神经网络权值调整的方法,再通过优化后的神经网络,探索图书各种属性与是否购买之间的潜在关系,从而实现图书是否购买的预测分类。仿真实验表明,该模型具有良好的预测性能和泛化能力,值得推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of book purchasing model based on improved genetic neural network
A modeling method based on genetic neural network used for book purchasing is put forward on account of lacking of a set of scientific and uniform purchasing mode and model in current book purchasing process. This method improves standard genetic algorithm first, and then uses the improved standard genetic algorithm as a method of feed forward neural network training and threshold value of feed forward neural network weight adjustment, after that, explores potential relationship between various properties of book and whether it is purchased or not through optimized neural network, thereby to realize the forecast classification whether the book should be purchased or not. Simulation experiment shows good forecast performance and generalization ability of the book purchasing model, thus it is worth for promotion.
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