{"title":"基于神经网络的高速公路应急资源需求预测","authors":"Liu Jin","doi":"10.1109/ICDMA.2013.140","DOIUrl":null,"url":null,"abstract":"Expressway traffic accidents seriously threaten the personal property security. And emergency resources are the basis and premise of accident rescue. Thus the emergency resource demand prediction of expressway is of great significance. The influence factors of emergency resource demand is analyzed in this paper, and neural network programming is carried out on the highway emergency resource demand. Finally, combining trained of neural network and case analysis, it achieves emergency resource demand projections for the new case of the emergency center. The results show that the BP neural network can form the inherent law of highway emergency resource demand after training, self-learning and self-adaptation, and the results can meet the prediction error precision. So the results of neural network prediction can provide scientific allocation of expressway emergency resource with reasonable reference.","PeriodicalId":403312,"journal":{"name":"2013 Fourth International Conference on Digital Manufacturing & Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Expressway Emergency Resources Demand Forecasting Based on Neural Network\",\"authors\":\"Liu Jin\",\"doi\":\"10.1109/ICDMA.2013.140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Expressway traffic accidents seriously threaten the personal property security. And emergency resources are the basis and premise of accident rescue. Thus the emergency resource demand prediction of expressway is of great significance. The influence factors of emergency resource demand is analyzed in this paper, and neural network programming is carried out on the highway emergency resource demand. Finally, combining trained of neural network and case analysis, it achieves emergency resource demand projections for the new case of the emergency center. The results show that the BP neural network can form the inherent law of highway emergency resource demand after training, self-learning and self-adaptation, and the results can meet the prediction error precision. So the results of neural network prediction can provide scientific allocation of expressway emergency resource with reasonable reference.\",\"PeriodicalId\":403312,\"journal\":{\"name\":\"2013 Fourth International Conference on Digital Manufacturing & Automation\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth International Conference on Digital Manufacturing & Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMA.2013.140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Digital Manufacturing & Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMA.2013.140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Expressway Emergency Resources Demand Forecasting Based on Neural Network
Expressway traffic accidents seriously threaten the personal property security. And emergency resources are the basis and premise of accident rescue. Thus the emergency resource demand prediction of expressway is of great significance. The influence factors of emergency resource demand is analyzed in this paper, and neural network programming is carried out on the highway emergency resource demand. Finally, combining trained of neural network and case analysis, it achieves emergency resource demand projections for the new case of the emergency center. The results show that the BP neural network can form the inherent law of highway emergency resource demand after training, self-learning and self-adaptation, and the results can meet the prediction error precision. So the results of neural network prediction can provide scientific allocation of expressway emergency resource with reasonable reference.