Group Daily Arrival Prediction Based on A Hybrid Model Combing Autoregressive Integrated Moving Average Model and Back Propagation Neural Network

Xiaoling Zhu, Xi Zhang, Ge Shi, Yashen Wang
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Abstract

To solve the problem of predicting daily arrival number of people belonging to a specific group, this paper proposes a hybrid model which integrates linear component (from ARIMA model) with non-linear component (from BP neural network). The experimental results indicate that, hybrid methodology that has both linear and nonlinear modeling capabilities is a good strategy for practical use.
基于自回归综合移动平均模型与反向传播神经网络相结合的混合模型的群体日到达预测
为解决特定群体日到达人数的预测问题,本文提出了一种将线性分量(来自ARIMA模型)与非线性分量(来自BP神经网络)相结合的混合模型。实验结果表明,同时具有线性和非线性建模能力的混合方法是一种很好的实际应用策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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