Assessing Residual Value of Heavy Construction Equipment Using Predictive Data Mining Model-Reference-Cited by-同舟云学术

Assessing Residual Value of Heavy Construction Equipment Using Predictive Data Mining Model

Published:2008-05 Issue:3 Volume:22 Page:181-191
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Fan Hongqin¹²³⁴,AbouRizk Simaan¹²³⁴,Kim Hyoungkwan¹²³⁴,Zaïane Osmar¹²³⁴

Affiliation:

1. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton AB T6G 2W2, Canada. E-mail: hfan@ualberta.ca

2. Chair, NSERFC/Alberta Construction Industry Research Chair, Professor, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton AB T6G 2W2, Canada. E-mail: abouRizk@ualberta.ca

3. Assistant Professor, Dept. of Civil and Environmental Engineering, Yonsei Univ., Seoul 120-749 (corresponding author). E-mail: hyoungkwan@yonsei.ac.kr

4. Associate Professor, Dept. of Computing Science, Univ. of Alberta, Edmonton AB T6G 2E8, Canada. E-mail: zaiane@cs.ualberta.ca

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290887-3801%282008%2922%3A3%28181%29

Reference31 articles.

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4. Predicting the Outcome of Construction Litigation Using Boosted Decision Trees

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