Ke Lv, Shoupeng Wang, Yan Zhang, Libin Zhang, Yulian Xi, Zhouyue Ling
{"title":"基于GA-BP神经网络的变电站工程造价评估","authors":"Ke Lv, Shoupeng Wang, Yan Zhang, Libin Zhang, Yulian Xi, Zhouyue Ling","doi":"10.1109/ICPET55165.2022.9918210","DOIUrl":null,"url":null,"abstract":"This paper takes the influencing factors of substation project cost as the input variable and the cost evaluation value as the output result, and then uses the neural network algorithm to evaluate the cost. Considering the shortcomings of neural network algorithm, genetic algorithm (GA) is used to optimize the neural network to realize a stable and effective evaluation of substation project cost. The simulation is carried out in Matlab environment, and the proposed algorithm is compared with the traditional BP neural network. The results show that the model improved by GA has more remarkable effect in application, and can guide the project cost management.","PeriodicalId":355634,"journal":{"name":"2022 4th International Conference on Power and Energy Technology (ICPET)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cost Evaluation of Substation Project Based on GA-BP Neural Network\",\"authors\":\"Ke Lv, Shoupeng Wang, Yan Zhang, Libin Zhang, Yulian Xi, Zhouyue Ling\",\"doi\":\"10.1109/ICPET55165.2022.9918210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper takes the influencing factors of substation project cost as the input variable and the cost evaluation value as the output result, and then uses the neural network algorithm to evaluate the cost. Considering the shortcomings of neural network algorithm, genetic algorithm (GA) is used to optimize the neural network to realize a stable and effective evaluation of substation project cost. The simulation is carried out in Matlab environment, and the proposed algorithm is compared with the traditional BP neural network. The results show that the model improved by GA has more remarkable effect in application, and can guide the project cost management.\",\"PeriodicalId\":355634,\"journal\":{\"name\":\"2022 4th International Conference on Power and Energy Technology (ICPET)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 4th International Conference on Power and Energy Technology (ICPET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPET55165.2022.9918210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Power and Energy Technology (ICPET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPET55165.2022.9918210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cost Evaluation of Substation Project Based on GA-BP Neural Network
This paper takes the influencing factors of substation project cost as the input variable and the cost evaluation value as the output result, and then uses the neural network algorithm to evaluate the cost. Considering the shortcomings of neural network algorithm, genetic algorithm (GA) is used to optimize the neural network to realize a stable and effective evaluation of substation project cost. The simulation is carried out in Matlab environment, and the proposed algorithm is compared with the traditional BP neural network. The results show that the model improved by GA has more remarkable effect in application, and can guide the project cost management.