摘要
本文在分析遗传算法和BP神经网络算法特点的基础上,建立了基于GA-BP的装备配件需求数量预测模型,并作了实例分析,表明装备配件需求预测模型的有效性和实用性。所给出的模型为装备配件及相关材料需求量的预测分析提供了一条新途径。
Based on the analysis of genetic algorithm and BP neural network algorithm, forecasting model of equipment parts demand is established based on the GA-BP, and a case study, demonstrates the validity and practicability of equipment spare parts demand prediction model. This model provides a new way for the prediction and analysis of equipment accessories and related materials demand.
出处
《价值工程》
2015年第32期100-102,共3页
Value Engineering
关键词
遗传算法
人工神经网络
配件需求
预测
genetic algorithm
artificial neural network
the demand for equipment spare parts
forecast
