Case Adaptation Method of Case-Based Reasoning for Construction Cost Estimation in Korea
Publication: Journal of Construction Engineering and Management
Volume 138, Issue 1
Abstract
Case-based reasoning (CBR) utilizes old solutions to solve a present problem. However, as no past situation is ever exactly the same as a new one, old solutions should be fitted for new circumstances, which is called case adaptation. Thus, the success of CBR depends on the ability of case adaptation. Generally, the case adaptation method can be categorized by two methods: decreasing the need for adaptation and increasing the capability. Nevertheless, previous research has focused on applying the method itself and rarely examined the adaptation or candidates selection. As an effort to enhance the performance of CBR, this research develops a case adaptation method that is balanced for both methods. To validate the method, a CBR cost model was developed that has an adaptation function using 129 military barrack projects in Korea, and then the method was tested by using 13 test cases. Furthermore, an applicability test was conducted based on 164 Korean public apartment projects.
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Acknowledgments
This research was supported by grants (UNSPECIFIEDR&D06CIT-A03 and UNSPECIFIEDVC-10) from the Korea Ministry of Land, Transport, and Marine Affairs.
References
Ahn, H., Kim, K.-J., and Han, I. (2006). “Global optimization of feature weights and the number of neighbors that combine in a case-based reasoning system.” Expert Syst., 23(5), 290–301.
An, S.-H., Kim, G.-H., and Kang, K.-I. (2007). “A case-based reasoning cost estimating model using experience by analytic hierarchy process.” Build. Environ., 42(7), 2573–2579.
Arditi, D., and Tokdemir, O. B. (1999). “Using case-based reasoning to predict the outcome of construction litigation.” Comput. Aided Civ. Infrastruct. Eng., 14(6), 385–393.
Barletta, R. (1994). “A hybrid indexing and retrieval strategy for advisory CBR system built with ReMind.” Proc., 2nd European Workshop on Case-Based Reasoning, Springer, Berlin Heidelberg, Germany, 49–58.
Boerner, K. (1994). “Structural similarity as guidance in case-based design.” Topics in case-based reasoning, S. Wees, K. Althoff, and M. Richter, eds., Springer Verlag, Berlin, 197–208.
Burkhard, H.-D. (2001). “Similarity and distance in case based reasoning.” Fundamenta Informaticae, 47(3-4), 201–215.
Chou, J.-S. (2009). “Web-based CBR system applied to early cost budgeting for pavement maintenance project.” Expert Syst. Appl., 36(2), 2947–2960.
Chua, D. K. H., Li, D. Z., and Chan, W. T. (2001). “Case-based reasoning approach in bid decision making.” J. Constr. Eng. Manage., 127(1), 35–45.
Chua, D. K. H., and Loh, P. K. (2006). “CB-contract: Case-based reasoning approach to construction contract strategy formulation.” J. Comput. Civ. Eng., 20(5), 339–350.
Dussart, C., Pommier, P., Siranyan, V., Grelaud, G., and Dussart, S. (2008). “Optimizing clinical practice with case-based reasoning approach.” J. Eval. Clin. Pract., 14(5), 718–720.
Evolver 4.0 [Computer software]. Palisade Corp., Ithaca, NY.
Funk, P., and Xiong, N. (2006). “Case-based reasoning and knowledge discovery in medical applications with time series.” Comput. Intell., 22(3-4), 238–253.
Goh, Y. M., and Chua, D. K. H. (2010). “Case-based reasoning approach to construction safety hazard identification: Adaptation and utilization.” J. Constr. Eng. Manage., 136(2), 170–178.
Graza, J., and Rouhana, K. (1995). “Neural network versus parameter based application in cost.” Cost Eng., 37(2), 14–18.
Hammond, K. J. (1989). Case-based planning: Viewing planning as a memory task, Academic, San Diego.
Han, J., and Kamber, M. (2003). Data mining—Concept and techniques, Freedom Academy, Seoul, 147–160 (in Korean).
Han, S.-G., Lee, S.-G., and Jo, G.-S. (2005). “Case-based tutoring system for procedural problem solving on the www.” Expert Syst. Appl., 29(3), 573–582.
Hegazy, T., and Ayed, A. (1998). “Neural network model for parametric cost estimating of highway projects.” J. Constr. Eng. Manage., 124(3), 210–218.
Huang, M.-J., Chen, M.-Y., and Lee, S.-C. (2007). “Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis.” Expert Syst. Appl., 32(3), 856–867.
Hüllermeier, E. (2007). Case-based approximate reasoning, Springer, Dordrecht, Netherlands, 30–31.
Ji, S.-H., Park, M., Lee, H.-S. (2010). “Data preprocessing-based parametric cost model for building projects: Case studies of Korean construction projects.” J. Constr. Eng. Manage., 136(8), 844–853.
Ji, S.-H., Park, M., Lee, H.-S. (2011a). “Cost estimation model for building projects using case-based reasoning.” Can. J. Civ. Eng., 38(5), 570–581.
Ji, S.-H., Park, M., Lee, H.-S., Ahn, J., Kim, N., and Son, B. (2011b). “Military facility cost estimation system using case-based reasoning in Korea.” J. Comput. Civ. Eng., 25(3), 218–231.
Jrade, A., and Alkass, S. (2007). “Computer-integrated system for estimating the costs of building projects.” J. Archit. Eng., 13(4), 205–223.
Karshenas, S., and Tse, J. (2002). “A case-based reasoning approach to construction cost estimating.” Proc., Int. Workshop on Information Technology in Civil Engineering 2002, ASCE, Reston, VA, 113–123.
Kolodner, J. (1991). “Improving human decision making through case-based decision aiding.” AI Mag., 12(2), 52–68.
Kolodner, J. (1993). Case-based reasoning, Kaufmann, San Francisco, 394–395.
Koo, C.-W., Hong, T.-H., Hyun, C.-T., and Koo, K.-J. (2010a). “A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects.” Can. J. Civ. Eng., 37(5), 739–752.
Koo, C-W., Hong, T.-H., Hyun, C.-T., Park, S. H., and Seo, J.-O. (2010b). “A study on the development of a cost model based on the owner’s decision making at the early stages of a construction project.” Int. J. Strategic Prop. Manage., 14(2), 121–137.
Kwan, S. H. (2008). Multivariate data analysis and application, Freedom Academy, Seoul, 72.
Leake, D., ed. (1996). “Case-based reasoning: In context.” Case-based reasoning experience, lessons, and future directions, AAAI Press/The MIT Press, Menlo Park, NJ, 3–30.
Lowe, D. J., Emsley, M. W., and Harding A., (2006). “Predicting construction cost using multiple regression techniques.” J. Constr. Eng. Manage., 132(7), 750–758.
Mark, F., Simoudis, E., and Hinkle, D. (1996). “Case-based reasoning: Expectations and results.” Case-based reasoning experience, lessons, and future directions, D. B. Leake, ed., AAAI Press/The MIT Press, 269–294.
Mitchell, T. M. (1997). Machine Learning, McGraw-Hill, Singapore, 231–232.
Morcous, G. Rivard, H., and Hanna, A. M. (2002). “Case-based reasoning system for modeling infrastructure deterioration.” J. Comput. Civ. Eng., 16(2), 104–114.
Oberlender, G. D., and Trost, S. M. (2001). “Predicting accuracy of early cost estimates based on estimate quality.” J. Constr. Eng. Manage., 127(3), 173–182.
Ozorhon, B., Dikman, I., and Birgonul, M. T. (2006). “Case-based reasoning model for international market selection.” J. Constr. Eng. Manage., 132(9), 940–948.
Pal, S. K., and Shiu, S. C. K. (2004). Foundations of soft case-based reasoning, Wiley Interscience, Hoboken, NJ.
Park, Y.-J., Kim, B.-C., and Chun, S.-H. (2006). “New knowledge extraction technique using probability for case-based reasoning: Application to medical diagnosis.” Expert Syst., 23(1), 2–20.
Qian, Z., Gao, W. S., Wang, F., and Yan, Z. (2009). “A case-based reasoning approach to power transformer fault diagnosis using dissolved gas analysis data.” Eur. Trans. Electr. Power, 19(3), 518–530.
Ryu, H.-G., Lee, H.-S., and Park, M. (2007). “Construction planning method using case-based reasoning (CONPLA-CBR).” J. Comput. Civ. Eng., 21(6), 410–422.
Salkind, N. J. (2009). Exploring research, Prentice Hall, New York, 5–9.
Schank, R. C. (1982). Dynamic memory: A theory of learning in computers and people, Cambridge University, New York.
Sharma, S. (1996). Applied multivariate techniques, Wiley, New York, 58–72.
Smyth, B., and Keane, M. (1995). “Experiments on adaptation-guided retrieval in a case-based design system.” Case-based reasoning research and development, M. Velso and A. Aamodt, eds., Springer Verlag, New York, 313–324.
Soutos, M., and Lowe, D. J. (2005). “Procost—Towards a powerful early stage cost estimating tool.” Proc., 2005 ASCE Int. Conf. on Computing in Civil Engineering , ASCE, Reston, VA.
Sun, B., Xu, L. D., Pei, X., and Li, H. (2003). “Scenario-based knowledge representation in case-based reasoning systems.” Expert Syst., 20(2), 92–99.
Tah, J. H. M., Carr, V., and Howes, R. (1998). “An application of case-based reasoning to the planning of highway bridge construction.” Eng., Constr., Archit. Manage., 5(4), 327–338.
Yau, N.-J., and Yang, J.-B. (1998). “Case-based reasoning in construction management.” Comput. Aided Civ. Infrastruct. Eng., 13(2), 143–150.
Yi, J. (2006). “A study on case-based forecasting model for monthly expenditures of residential building project.” Korean J. Constr. Eng. Manage., 79(1), 128–137.
Zhuang, Z. Y., Churilov, L., Burstein, F., and Sikaris, K. (2009). “Combining data mining and case-based reasoning for intelligent decision support for pathology ordering by general practitioners.” Eur. J. Oper. Res., 195(3), 662–675.
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Published In
Journal of Construction Engineering and Management
Volume 138 • Issue 1 • January 2012
Pages: 43 - 52
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Jul 20, 2010
Accepted: Apr 16, 2011
Published online: Jul 28, 2011
Published in print: Jan 1, 2012
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