[1]涂胜红,陈宏伟,杨威威,等. 基于分布式混合灰狼蝗虫优化算法航班延误预测[J].湖北工业大学学报,2021,(5):51-54.
　TU Shenghong,CHEN Hongwei,YANG Weiwei,et al. Flight Delay Prediction Based on Distributed Hybrid Gray Wolf Grasshopper Optimization Algorithm[J].,2021,(5):51-54.
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 基于分布式混合灰狼蝗虫优化算法航班延误预测()
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
期数:
2021年第5期
页码:
51-54
栏目:
湖北工业大学学报
出版日期:
2021-10-31

文章信息/Info

Title:
 Flight Delay Prediction Based on Distributed Hybrid Gray Wolf Grasshopper Optimization Algorithm
文章编号:
1003-4684(2021)05-0051-04
作者:
 涂胜红;  陈宏伟;  杨威威;  杨智慧
 湖北工业大学计算机学院， 湖北 武汉 430068
Author(s):
 TU Shenghong; CHEN Hongwei;  YANG Weiwei;  YANG Zhihui
 School of Computer Science, Hubei Univ. of Tech., Wuhan 430068, China
关键词:
 ; 蝗虫优化算法;  灰狼优化算法;  分布式混合算法模型;  航班延误预测
Keywords:
 ; grasshopper optimization algorithm;  grey wolf optimization;  distributed hybrid algorithm model;  flight delay prediction
分类号:
TP391
文献标志码:
A
摘要:
 针对航班延误成因复杂、数据量大，传统模型预测准确率差、效率低的问题，提出一种基于灰狼优化算法和蝗虫优化算法的混合算法建立航班延误预测模型。将灰狼优化算法的等级机制引入到蝗虫优化算法中，在种群迭代时生成不同层级狼群共同指导种群的进化方法，避免单个体对种群进化的绝对控制。采用Spark大数据框架设计分布式混合灰狼蝗虫优化算法提高模型运行效率。仿真实验结果表明：分布式混合灰狼蝗虫算法能够提高航班延误预测准确率和运行效率。
Abstract:
 Aiming at the problems of complicated flight delays, large amount of data and poor prediction accuracy and low efficiency of traditional models, a hybrid algorithm based on gray wolf optimization algorithm and grasshopper optimization algorithm is proposed to establish a flight delay prediction model. The level mechanism of gray wolf optimization algorithm is introduced into the grasshopper optimization algorithm to generate different levels of wolves to jointly guide the evolution of the population when the population is iterated, so as to avoid the absolute control of the evolution of the population by a single body. The Spark big data framework is used to design a distributed hybrid gray wolf grasshopper optimization algorithm to improve model operation efficiency. The simulation experiment results show that the distributed hybrid gray wolf grasshopper algorithm can improve the accuracy of flight delay prediction and operational efficiency.

参考文献/References:

[1] NIU B,DAI Z,ZHUO X.Co-opetition effect of promised-delivery-time sensitive demand on air cargo carriers’ big data investment and demand signal sharing decisions[J].Transportation Research Part E:Logistics and Transportation Review,2019,23(MAR):29-44.
[2] 杜亚倩,张聊东.我国航班延误的现状及应对措施[J].中国科技信息,2020(21):35-37.
[3] KHANMOHAMMADI S, TUTUN S, KUCUK Y.A new multilevel input layer artificial neural network for predicting flight delays at JFK airport[J]. Procedia Computer Science, 2016, 95:237-244.
[4] YAZDI M F, KAMEL S R, CHABOK S, et al. Flight delay prediction based on deep learning and Levenberg-marquart algorithm[J]. Journal of Big Data, 2020,7(1):51-63.
[5] YU B,GUO Z,ASIAN S,et al.Flight delay prediction for commercial air transport:A deep learning approach[J].Transportation Research Part E:Logistics and Transportation Review,2019,125(MAY):203-221.
[6] 李华峰.枢纽机场大面积航班延误波及传递模型的研究[D].天津:中国民航大学, 2012.
[7] 张兆宁,张佳.大面积航班延误发生的预测方法[J].系统工程,2020,38(4):115-121.
[8] 王语桐,朱金福,马思思.基于支持向量回归和线性回归的航班延误组合预测[J].武汉理工大学学报(交通科学与工程版),2019,43(3):426-431.

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备注/Memo

备注/Memo:
 ［收稿日期］ 2021-03-23
［基金项目］ 国家自然科学基金（61772180）; 湖北省大学生创新创业项目（S201910500048）
［第一作者］ 涂胜红(1996-)， 男，湖北广水人，湖北工业大学硕士研究生，研究方向为大数据，云计算
［通信作者］ 陈宏伟(1975-)， 男，湖北武汉人，工学博士，湖北工业大学教授，研究方为大数据，云计算
更新日期/Last Update: 2021-11-01