在电子投标中应用深度学习的投标价格预测

Dae-Hyeon Hwang, Bae Young Chul
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引用次数: 0

摘要

招标程序采用收集的招标信息和公共/私营部门累计招标结果的统计分析方法;然而,采用多次摇号的中标法预测准确的投标价格并不容易。为此,本文分析了2015年1月至2019年8月电力工程投标的现状数据的准确性,利用MLP和RNN方法,通过预测第一和最低投标人之间的金额,提出了一种预测中标所需的投标金额的技术。
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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.
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