{"title":"在电子投标中应用深度学习的投标价格预测","authors":"Dae-Hyeon Hwang, Bae Young Chul","doi":"10.13067/JKIECS.2020.15.1.147","DOIUrl":null,"url":null,"abstract":"The bidding program uses statistical analysis method of the collected bidding information and the accumulated bidding results from the public/private sector; however, it is not easy to predict the accurate bidding price by winning the bid method through multiple lottery. Therefore, this paper analyzes the accuracy of the current state data of the electric construction bid from January 2015 to August 2019 acquired from the electric net, which is an electronic bidding site, We use MLP and RNN method, and proposes a technique to predict the bidding amount necessary for the winning bid by predicting the amount between the first and the lowest bidder.","PeriodicalId":22843,"journal":{"name":"The Journal of the Korea institute of electronic communication sciences","volume":"38 1","pages":"147-152"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The prediction of bidding price using deep learning in the electronic bidding\",\"authors\":\"Dae-Hyeon Hwang, Bae Young Chul\",\"doi\":\"10.13067/JKIECS.2020.15.1.147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The bidding program uses statistical analysis method of the collected bidding information and the accumulated bidding results from the public/private sector; however, it is not easy to predict the accurate bidding price by winning the bid method through multiple lottery. Therefore, this paper analyzes the accuracy of the current state data of the electric construction bid from January 2015 to August 2019 acquired from the electric net, which is an electronic bidding site, We use MLP and RNN method, and proposes a technique to predict the bidding amount necessary for the winning bid by predicting the amount between the first and the lowest bidder.\",\"PeriodicalId\":22843,\"journal\":{\"name\":\"The Journal of the Korea institute of electronic communication sciences\",\"volume\":\"38 1\",\"pages\":\"147-152\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of the Korea institute of electronic communication sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13067/JKIECS.2020.15.1.147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of the Korea institute of electronic communication sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13067/JKIECS.2020.15.1.147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The prediction of bidding price using deep learning in the electronic bidding
The bidding program uses statistical analysis method of the collected bidding information and the accumulated bidding results from the public/private sector; however, it is not easy to predict the accurate bidding price by winning the bid method through multiple lottery. Therefore, this paper analyzes the accuracy of the current state data of the electric construction bid from January 2015 to August 2019 acquired from the electric net, which is an electronic bidding site, We use MLP and RNN method, and proposes a technique to predict the bidding amount necessary for the winning bid by predicting the amount between the first and the lowest bidder.