Adaptive Learning of Contractor Default Prediction Model for Surety Bonding-Reference-Cited by-同舟云学术

Adaptive Learning of Contractor Default Prediction Model for Surety Bonding

Published:2013-06 Issue:6 Volume:139 Page:694-704
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Awad Adel¹,Fayek Aminah Robinson²

Affiliation:

1. Postdoctoral Fellow, Hole School of Construction Engineering, Dept. of Civil and Environmental Engineering, 1-050 Markin/CNRL Natural Resources Engineering Facility, Univ. of Alberta, Edmonton, Alberta, Canada T6G 2W2.

2. Professor, NSERC Industrial Research Chair in Strategic Construction Modeling and Delivery, Ledcor Professor in Construction Engineering, Hole School of Construction Engineering, Dept. of Civil and Environmental Engineering, 3-013 Markin/CNRL Natural Resources Engineering Facility, Univ. of Alberta, Edmonton, Alberta, Canada T6G 2W2 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0000639

Reference24 articles.

1. Adaptation of Fuzzy Inference System Using Neural Learning

2. Managing Owner’s Risk of Contractor Default

3. Determination of fuzzy logic membership functions using genetic algorithms

4. Arun K. Shakti K. and Kumar R. G. (2007). “A comparison of computational efforts between particle swarm optimization and genetic algorithm for identification of fuzzy models.” Proc. NAFIPS ’07 Annual Meeting of the North American Fuzzy Information Processing Society IEEE New York 245–250.

5. Awad A. and Fayek A. R. (2011). “Adaptive learning for fuzzy expert systems for construction applications.” CSCE Annual General Conf. Canadian Society for Civil Engineering Quebec Canada.

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