舰船运输与补给需求预测问题研究

Peng Dong, Peng Yu, Furong Qin
{"title":"舰船运输与补给需求预测问题研究","authors":"Peng Dong, Peng Yu, Furong Qin","doi":"10.1109/ICISCE.2016.148","DOIUrl":null,"url":null,"abstract":"To solve the problems of demand forecasting, the case-based reasoning (CBR) is used to create samples, and the least squares support vector machines (LSSVM) model is used as forecasting model, then the anti-air ammo demand forecasting in island offensive operation is taken as an empirical analysis. The result indicates that the samples created by case-based reasoning are available, and the forecasting results of different models are consilient but more accurate, this method can solve the problem of the lack of samples, so it is applicable to the combat supplies demand forecasting.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on Transportation and Replenishment Demand Forecasting Problem of Naval Warship\",\"authors\":\"Peng Dong, Peng Yu, Furong Qin\",\"doi\":\"10.1109/ICISCE.2016.148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problems of demand forecasting, the case-based reasoning (CBR) is used to create samples, and the least squares support vector machines (LSSVM) model is used as forecasting model, then the anti-air ammo demand forecasting in island offensive operation is taken as an empirical analysis. The result indicates that the samples created by case-based reasoning are available, and the forecasting results of different models are consilient but more accurate, this method can solve the problem of the lack of samples, so it is applicable to the combat supplies demand forecasting.\",\"PeriodicalId\":6882,\"journal\":{\"name\":\"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCE.2016.148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCE.2016.148","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

针对需求预测问题,采用基于案例推理(case-based reasoning, CBR)方法生成样本,采用最小二乘支持向量机(least squares support vector machines, LSSVM)模型作为预测模型,对海岛进攻作战防空弹药需求预测进行实证分析。结果表明,基于案例推理生成的样本是可用的,不同模型的预测结果一致且更准确,该方法解决了样本不足的问题,适用于作战物资需求预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Transportation and Replenishment Demand Forecasting Problem of Naval Warship
To solve the problems of demand forecasting, the case-based reasoning (CBR) is used to create samples, and the least squares support vector machines (LSSVM) model is used as forecasting model, then the anti-air ammo demand forecasting in island offensive operation is taken as an empirical analysis. The result indicates that the samples created by case-based reasoning are available, and the forecasting results of different models are consilient but more accurate, this method can solve the problem of the lack of samples, so it is applicable to the combat supplies demand forecasting.
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