基于最小二乘支持向量机的飞行事故建模与预测

Gan Xusheng, Duanmu Jingshun, Cong Wei
{"title":"基于最小二乘支持向量机的飞行事故建模与预测","authors":"Gan Xusheng, Duanmu Jingshun, Cong Wei","doi":"10.1109/ICEIT.2010.5608379","DOIUrl":null,"url":null,"abstract":"To analyze and predict the flight safety situation scientifically, a flight accident prediction model, based on least squares support vector machine (LS-SVM), is proposed. Simultaneously, three steps grid search method is introduced into the flight accident modeling to select efficiently the parameters of LS-SVM. The simulation results of modeling and predicting on flight accident 100000-hour-rate indicate that, LS-SVM model and its parameter selection method are feasible and effective in flight accident prediction.","PeriodicalId":346498,"journal":{"name":"2010 International Conference on Educational and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Flight accident modeling and predicting based on least squares support vector machine\",\"authors\":\"Gan Xusheng, Duanmu Jingshun, Cong Wei\",\"doi\":\"10.1109/ICEIT.2010.5608379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To analyze and predict the flight safety situation scientifically, a flight accident prediction model, based on least squares support vector machine (LS-SVM), is proposed. Simultaneously, three steps grid search method is introduced into the flight accident modeling to select efficiently the parameters of LS-SVM. The simulation results of modeling and predicting on flight accident 100000-hour-rate indicate that, LS-SVM model and its parameter selection method are feasible and effective in flight accident prediction.\",\"PeriodicalId\":346498,\"journal\":{\"name\":\"2010 International Conference on Educational and Information Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Educational and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEIT.2010.5608379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Educational and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIT.2010.5608379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

为了科学地分析和预测飞行安全状况,提出了一种基于最小二乘支持向量机(LS-SVM)的飞行事故预测模型。同时,将三步网格搜索方法引入到飞行事故建模中,有效地选择LS-SVM的参数。100,000小时率飞行事故建模与预测的仿真结果表明,LS-SVM模型及其参数选择方法在飞行事故预测中是可行和有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flight accident modeling and predicting based on least squares support vector machine
To analyze and predict the flight safety situation scientifically, a flight accident prediction model, based on least squares support vector machine (LS-SVM), is proposed. Simultaneously, three steps grid search method is introduced into the flight accident modeling to select efficiently the parameters of LS-SVM. The simulation results of modeling and predicting on flight accident 100000-hour-rate indicate that, LS-SVM model and its parameter selection method are feasible and effective in flight accident prediction.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信