基于PSO-BP的煤炭企业物流成本预测

Q4 Multidisciplinary 辽宁工程技术大学学报(自然科学版) Pub Date : 2010-12-01 DOI:10.5503/J.CL.2010.01.007

Yong-kui Shi, Jian-sheng Shao

{"title":"基于PSO-BP的煤炭企业物流成本预测","authors":"Yong-kui Shi, Jian-sheng Shao","doi":"10.5503/J.CL.2010.01.007","DOIUrl":null,"url":null,"abstract":"In order to forecast the logistics cost of coal enterprises effectively,the PSO-BP and BP network are respectively used to forecast the logistics cost ,the result shows that the PSO-BP network's convergence speed and prediction accuracy are obvious better than BP network. The PSO-BP neural network is very attractive for a wide application in forecasting logistics cost in coal enterprises.","PeriodicalId":35059,"journal":{"name":"辽宁工程技术大学学报(自然科学版)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The forecast of logistics cost of coal enterprises based on PSO-BP\",\"authors\":\"Yong-kui Shi, Jian-sheng Shao\",\"doi\":\"10.5503/J.CL.2010.01.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to forecast the logistics cost of coal enterprises effectively,the PSO-BP and BP network are respectively used to forecast the logistics cost ,the result shows that the PSO-BP network's convergence speed and prediction accuracy are obvious better than BP network. The PSO-BP neural network is very attractive for a wide application in forecasting logistics cost in coal enterprises.\",\"PeriodicalId\":35059,\"journal\":{\"name\":\"辽宁工程技术大学学报(自然科学版)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"辽宁工程技术大学学报(自然科学版)\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.5503/J.CL.2010.01.007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Multidisciplinary\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"辽宁工程技术大学学报(自然科学版)","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.5503/J.CL.2010.01.007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Multidisciplinary","Score":null,"Total":0}

引用次数: 1

摘要

为了有效地预测煤炭企业的物流成本，分别采用PSO-BP和BP网络对煤炭企业的物流成本进行预测，结果表明，PSO-BP网络的收敛速度和预测精度明显优于BP网络。PSO-BP神经网络在煤炭企业物流成本预测中具有广泛的应用前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

The forecast of logistics cost of coal enterprises based on PSO-BP

In order to forecast the logistics cost of coal enterprises effectively,the PSO-BP and BP network are respectively used to forecast the logistics cost ,the result shows that the PSO-BP network's convergence speed and prediction accuracy are obvious better than BP network. The PSO-BP neural network is very attractive for a wide application in forecasting logistics cost in coal enterprises.

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