Representing the Knowledge of Public Construction Project Cost Estimator by Using Rule-Based Method

Abelrahman Osman Elfaki^1,2, Saleh Alatawi^1,2

¹University of Tabuk, Tabuk, KSA.
²Binladen Research Chair of Quality and Productivity Improvement in the Construction Industry, College of Engineering, University of Hail, Hail, KSA.

DOI: 10.4236/jbcpr.2015.34019                

Abstract

Despite the presence of various construction project cost estimate softwares, human experience and knowledge cannot be disregarded. This fact has been proven in practice, where the success of construction cost estimate process is mainly based on knowledge of human estimator. The main question concerns what human knowledge determines the success of the construction cost estimation process. To address this question we have applied Delphi technique and the output is eleven factors that are enough to precisely represent construction cost estimator knowledge. Then we have used First Order Logic (FOL) to represent these factors in terms of predicates and rules. These FOL rules could be used for evaluating construction cost estimator knowledge in five classes: fail, pass, acceptable, good, and very good. As a validation process we have done experiments using history data and the results have proved the accuracy of our proposed method.

Keywords

Construction Management, Construction Cost Estimation, Rule-Based System

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Holm, L., Schaufelberger, J.E., Griffin, D. and Cole, T. (2005) Construction Cost Estimating: Process and Practices. Pearson Education, Upper Saddle River.
[2]	Ma, Z., Liu, Z. and Wei, Z. (2015) Formalized Representation of Specifications for Construction Cost Estimation by Using Ontology. Computer-Aided Civil and Infrastructure Engineering, Published Online. http://dx.doi.org/10.1111/mice.12175
[3]	Flyvbjerg, B., Holm, M.S. and Buhl, S.L. (2002) Underestimating Costs in Public Works Projects: Error or Lie? Journal of the American Planning Association, 68, 279-295. http://dx.doi.org/10.1080/01944360208976273
[4]	Taroun, A. (2014) Towards a Better Modelling and Assessment of Construction Risk: Insights from a Literature Review. International Journal of Project Management, 32, 101-115. http://dx.doi.org/10.1016/j.ijproman.2013.03.004
[5]	Jing, D. and El-Gafy, M. (2015) Human Computation Enabled Organizational Learning in the Face of Deep Uncertainty: Example of Conceptual Estimating. Journal of Information Technology in Construction, 20, 275.
[6]	Peter, J. (1998) Introduction to Expert Systems. 3rd Edition, Addison Wesley, New York, 2.
[7]	French, S.S., Martin, F. and John, K. (2003) A Generic Feature Driven Activity-Based Cost Estimation Process. Advance Engineering Informatics, 17, 23-39. http://dx.doi.org/10.1016/S1474-0346(03)00017-X
[8]	Shane, S.J., Molenaar, K.R., Anderson, S. and Schexnayder, C. (2009) Construction Project Cost Escalation Factors. Journal of Management in Engineering, 25, 221-229. http://dx.doi.org/10.1061/(ASCE)0742-597X(2009)25:4(221)
[9]	Akinci, B. and Fischer, M. (1998) Factors Affecting Contractors’ Risk of Cost Overburden. Journal of Management in Engineering, 14, 67-77. http://dx.doi.org/10.1061/(ASCE)0742-597X(1998)14:1(67)
[10]	Elfaki, O.A., Alatawi, S. and Abushandi, E. (2014) Using Intelligent Techniques in Construction Project Cost Estimation: 10-Year Survey. Advances in Civil Engineering, 2014, Article ID: 107926. http://dx.doi.org/10.1155/2014/107926
[11]	Lewis, A. (2008) The Cambridge Handbook of Psychology and Economic Behaviour. Cambridge University Press, Cambridge. http://dx.doi.org/10.1017/CBO9780511490118
[12]	Rowe, G. and Wright, G. (2001) Expert Opinions in Forecasting. Role of the Delphi Technique. In: Armstrong, Ed., Principles of Forecasting: A Handbook of Researchers and Practitioners, Kluwer Academic Publishers, Boston.
[13]	Zavadskas, E.K., Vainiūnas, P., Turskis, Z. and Tamosaitiene, J. (2012) Multiple Criteria Decision Support System for Assessment of Projects Managers in Construction. International Journal of Information Technology & Decision Making, 11, 501-520. http://dx.doi.org/10.1142/S0219622012400135
[14]	Dainty, A. and Loosemore, M. (2012) Human Resource Management in Construction: Critical Perspectives. 2nd Edition, Routledge, New York.
[15]	Walicki, M. (2006) Introduction to Logic. Lecture Notes Online. http://www.econphd.net/notes.htm
[16]	Wielemaker, J. (2007) SWI-Prolog (Version 5.6.36). Free Software, University of Amsterdam, Amsterdam.