西南交通大学学报2018，Vol.53Issue(1)：206-213,8.DOI:10.3969/j.issn.0258-2724.2018.01.025
基于改进加权一阶局域法的空中交通流量预测模型
Air Traffic Flow Prediction Model Basedon Improved Adding-Weighted One-Rank Local-Region Method
摘要
Abstract
Accurate air traffic flow prediction is an important basis for efficient air traffic control and management.Aiming at the inherent chaotic dynamic characteristics of air traffic flow times eries,the chaotic traffic-flow time-series prediction model based on improved adding-weight one-rank local-region prediction method was analyzed herein.Firstly,an improved adding-weight one-rank local-region prediction method was proposed,which involved1 weighing the evolution of adjacent phase points.Further,the prediction results were corrected by construction of error sequences during the prediction process.Secondly,the chaotic characteristics were verified to exist in four groups of air traffic flow time series at different time scales,using the saturation phenomenon of correlation dimension.Finally,a validation experiment for air traffic flow prediction was carried out using the improved method,after phase space reconstruction of air traffic flow time series.The results show that the prediction accuracy of all four groups is improved,wherein the traffic flow time series with time scale of 10 min has the best precision;the relative error in this case reduces by 29.7％.关键词
混沌时间序列/相空间重构/加权一阶局域预测法/误差序列/空中交通流量预测Key words
chaotic time series/phase space reconstruction/adding-weight one-rank local-region prediction method/error sequence/air traffic flow prediction分类
航空航天引用本文复制引用
王超,朱明,赵元棣..基于改进加权一阶局域法的空中交通流量预测模型[J].西南交通大学学报,2018,53(1):206-213,8.基金项目
国家自然科学基金民航联合基金资助项目(U1533106,U1433111) （U1533106,U1433111）
