Computational intelligence techniques for building transparent construction performance models

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn 2, Issue , 2006, Pages 1166-1171

  Chen, L ^a   Pedrycz, W ^b   Chen, Philip ^a  

^a UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

^b UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL METHODS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; NEURAL NETWORKS;

CONSTRUCTION PERFORMANCE INDICATORS; DATA COLLECTION; GENERAL REGRESSION NEURAL NETWORKS (GRNN);

INTELLIGENT SYSTEMS;

EID: 34548119511     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2006.384558     Document Type: Conference Paper

References (12)

1. H. A. Bassioni, A. D. F. Price, and T. M. Hassan, Performance Measurement in Construction, Journal of Management in Engineering, 20(2): 42-50.
2. H.R. Thomas, and A.S Sakarcan, Forecasting Labor Productivity Using the Factor Model. Journal of Construction Engineering and Management, ASCE, 120(1): 228-239, 1994
3. R. Sonmez and J. E. Rowings, Construction Labor Productivity Modeling with Neural Networks, Journal of Construction Engineering and Management, 124(6): 498-504, 1998.
4. F. A. Robinson and S. Zhuo, A Fuzzy Expert System for Design Performance Prediction and Evaluation. Canadian Journal of Civil Engineering, CSCE, 28(1): 1-25, 2001
5. D.F. Specht, A Generalized Regression Neural Network, IEEE Transactions on Neural Networks, 2: 568-576, 1991
6. FAQ of Neural networks, http://www.faqs.org/faqs/aj-faq/neural-nets/ part2/section-21.html
7. D. F. Specht and H. Romsdahl, Experience with Adaptive Probabilistic Neural Networks and Adaptive General Regression Neural Networks. In Proceedings of IEEE International Conference on Neural Networks, Orlando, FL, 1994.
8. P.V. Yee, Regularized Radial Basis Function Networks: Theory and Applications to Probability Estimation, Classification, and Time Series Prediction, PHD Thesis, McMaster University, Hamilton, Ontario, 1998
9. T. Masters, Advanced Algorithms for Neural Networks: A C++ Sourcebook, New York, NY, John Wiley and Sons, 1995
10. F. Hoppner, F. Klawonn, R. Kruse, and T. Runklcr, Fuzzy Cluster Analysis. Chichester, Wiley, 1999
11. n Reconstruction Problem in Linguistic Interfaces, Proc. of IFSA 2005 - The International Fuzzy Systems Association World Congress, Beijing, China, July 28-31, 2005.
12. G.M. Dissanayake, Private Correspondence, 2004