한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
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전자입찰에서 딥러닝을 이용한 입찰 가격예측

The Prediction of Bidding Price using Deep Learning in the Electronic Bidding

  • 황대현 (전남대학교 전기 및 반도체공학과) ;
  • 배영철 (전남대학교 전기.전자통신.컴퓨터공학부)
  • 투고 : 2019.11.20
  • 심사 : 2020.02.15
  • 발행 : 2020.02.29
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초록

입찰프로그램은 민/관으로부터 고지되는 입찰 정보의 수집과 누적된 입찰결과의 통계적 분석방법을 사용하고 있지만 복수예가 추첨을 통한 낙찰방식으로 정확한 낙찰가를 예측하는 것은 쉽지 않다. 따라서 본 논문은 MLP, RNN 등의 방법을 이용하여 전자입찰 사이트인 전기넷에서 취득한 2015년 1월부터 2019년 8월까지 전기공사 낙찰현황 데이터의 정확도 등을 분석하고, 이를 통해 낙찰 하한가에 가장 근접하고 1순위 금액 사이의 금액을 예측하여 낙찰에 필요한 입찰금액을 예측하기 위한 기법을 제안한다.

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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참고문헌

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