基于聚类算法和ANFIS的广西航空货运量预测研究

Air Cargo Demand Forecast of Guangxi Based on Clustering Algorithm and ANFIS

自适应神经模糊推理系统(ANFIS)有着强大的非线性处理能力,可以有效地处理包括物流需求预测在内的非线性问题。运用广西航空货运量的指标体系,并结合基于聚类算法和ANFIS的广西航空货运量预测方法,对广西未来5年的航空物流货运量进行了预测。一方面,通过与其它算法进行对比,结合2004—2014年广西航空货运量的实例结果,证明了此预测方法的精确性与稳定性;另一方面,有利于管理决策者根据广西机场未来货运量的发展趋势及时制定机场改造方案,有效发挥广西在"一带一路"和中国东盟自由贸易区的战略作用。

Adaptive neural fuzzy inference system（ANFIS）has a strong nonlinear processing ability,it is an effective method to deal with nonlinear problem including logistics demand forecasting.This paper used the forecasting model,which is based on the clustering algorithm and ANFIS,to forecast the air cargo freight at Guangxi in the next 5years.Combined the comparison of other algorithms with air cargo demand from 2004—2014in Guangxi,its forecasting accuracy was proved,and its forecast for superior convergence speed and the air cargo demand is effective and feasible.