{"title":"基于混合遗传算法神经网络的路面性能评价模型","authors":"Wei-dong Qian","doi":"10.1109/CINC.2010.5643855","DOIUrl":null,"url":null,"abstract":"Road pavement perfoemance evaluation and prediction is two most important parts of pavement management system. In order to scientifically and accurately predict the future road pavement situation,evaluation indexes and main influence factors of pavement performance were analyzed. Then functional performance,structure performance, safety performance, and comfortability performance was selected as the evolution index and three factors were taken as parameters, including temperature, annual precipitation,annual average daily traffic. The two prediction models of BP neural network and hybrid algorithms based on neural network and genetic algorithm were built respectively. Forecasting result shows that neural network model based on genetic algorithms has higher prediction accuracy and more network generalization than those of BP neural network;","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Road pavement performance evaluation model based on hybrid genetic algorithm neural network\",\"authors\":\"Wei-dong Qian\",\"doi\":\"10.1109/CINC.2010.5643855\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Road pavement perfoemance evaluation and prediction is two most important parts of pavement management system. In order to scientifically and accurately predict the future road pavement situation,evaluation indexes and main influence factors of pavement performance were analyzed. Then functional performance,structure performance, safety performance, and comfortability performance was selected as the evolution index and three factors were taken as parameters, including temperature, annual precipitation,annual average daily traffic. The two prediction models of BP neural network and hybrid algorithms based on neural network and genetic algorithm were built respectively. Forecasting result shows that neural network model based on genetic algorithms has higher prediction accuracy and more network generalization than those of BP neural network;\",\"PeriodicalId\":227004,\"journal\":{\"name\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2010.5643855\",\"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 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Road pavement performance evaluation model based on hybrid genetic algorithm neural network
Road pavement perfoemance evaluation and prediction is two most important parts of pavement management system. In order to scientifically and accurately predict the future road pavement situation,evaluation indexes and main influence factors of pavement performance were analyzed. Then functional performance,structure performance, safety performance, and comfortability performance was selected as the evolution index and three factors were taken as parameters, including temperature, annual precipitation,annual average daily traffic. The two prediction models of BP neural network and hybrid algorithms based on neural network and genetic algorithm were built respectively. Forecasting result shows that neural network model based on genetic algorithms has higher prediction accuracy and more network generalization than those of BP neural network;