基于遗传神经网络预测模型的辽宁省物流需求预测

Forecast of logistics demand in Liaoning Province based on genetic neural network prediction model

针对目前物流需求预测不够准确的问题,以辽宁省物流需求为研究对象,通过分析影响物流需求相关因素,构建辽宁省物流需求预测指标体系,以公路货运量近似代替物流需求量,对公路货运量与物流需求预测指标体系中其他指标进行灰色关联度分析,分别采用神经网络预测模型、遗传算法神经网络预测模型对辽宁省物流需求进行预测。研究表明:遗传神经网络预测模型对辽宁省物流需求预测结果更为精确。研究结论为精准预测辽宁省物流需求提供参考。

Aiming at the problem that the logistics demand prediction is not accurate enough at present,this paper takes the logistics demand of Liaoning Province as the research object,analyzes the relevant factors affecting the logistics demand,constructs the logistics demand prediction index system of Liaoning Province,replaces the logistics demand approximately with the highway freight volume,and analyzes the gray correlation between the highway freight volume and other indicators in the logistics demand prediction index system.Using neural network prediction models and genetic algorithm neural network prediction models to predict logistics demand in Liaoning Province.Research has shown that the genetic neural network prediction model is more accurate in predicting logistics demand in Liaoning Province.The research conclusion provides a reference for accurately predicting logistics demand in Liaoning Province.