Forecasting methods and application of regional logistics demand based on wavelet neural network

Sun Ming, Wu Jing
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引用次数: 1

Abstract

Wavelet neural network is a neural network combining the wavelet theory with neural network theory, which avoids nonlinear optimization problems such as blindness of the design of BP neural network structure and local optimum, greatly simplifying the training. The use of wavelet neural networks to forecast regional logistics demand provided an important reference for regional logistics systematic planning and the rational allocation of logistic resources. Therefore, the use of regional economic indicators to forecast regional logistics demand had strong feasibility and promotes the coordinated development between regional logistics industry and regional economy. The model reveals nonlinear mapping relationship between the regional economy and regional logistics demand and provides a new idea and method for the regional logistics demand forecasting.
基于小波神经网络的区域物流需求预测方法及应用
小波神经网络是将小波理论与神经网络理论相结合的一种神经网络,避免了BP神经网络结构设计的盲目性和局部最优等非线性优化问题,极大地简化了训练。利用小波神经网络对区域物流需求进行预测,为区域物流系统规划和合理配置物流资源提供了重要参考。因此,利用区域经济指标预测区域物流需求具有较强的可行性,促进了区域物流业与区域经济的协调发展。该模型揭示了区域经济与区域物流需求之间的非线性映射关系,为区域物流需求预测提供了一种新的思路和方法。
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