A New Fuzzy Decision Support Method for Analysis of Economic Factors of Turkey's Construction Industry
Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.
[1] Tavakoli, A., Tulumen, S.C. 1990. "Construction Industry in Turkey".
Construction Management and Economics, Vol: 8, pp.77-87.
[2] Sanl─▒lar T. 1995. Quality Management in The Turkish Construction
Industry. M.Sc. Thesis, Boğaziçi University, Institute of Science,
132pp, Istanbul, Turkey
[3] Langford, D., Male, S., Strategic Management in Construction.
Blackwell Science, 250 pp., USA.
[4] Engineering News Record, 1994. Change in Bidding Law Could Aid
Turks Abroad, McGraw-Hill, pp. 27-8., New York.
[5] The Association of Turkish Construction Companies and Contractors
(ATCCC), 1995. Directory of Turkish Construction Contractors,
Ankara, Turkey.
[6] Erkut, H., 1992. "The Importance of Construction Industry in National
Economy and Effects of Construction Industry Management on
Economic Improvement". In: 3. ─░zmir Economy Congress, pp.91-103,
Izmir, Turkey.
[7] Engineering News Record, 1995. The Turkish Contractor - A Dynamic
Newcomer, pp. 1-12., New York.
[8] Yucel K. 1993. Cost of Rework in Construction for Maintaining Quality.
M.Sc. Thesis, Boğaziçi University, Institute of Science, 70pp, Istanbul,
Turkey
[9] Tur, R., 2003. Strategic Management of Construction Firms and Strategy
Formulation for The Sector. M.Sc. Thesis, Akdeniz University, Institute
of Science, 115pp, Antalya, Turkey
[10] Turkey-s Gazette, 2000. 2000 Planned Investments and Budget
Program, Ankara, Turkey.
[11] The Turkish Construction Catalog, 2003. The Turkish Society of Civil
Engineers (TSCE), Ankara, Turkey.
[12] The Central Bank of thr Republic of Turkey, 2003. "2003 Annual
Report", Ankara, Turkey.
[13] State Planning Organization (SPO), 1982. SPO Objects and Strategies
of Five Years Progress Plans. SPO Publications, 284pp, Ankara,
Turkey.
[14] The Ministry of Public Works and Resettlement-s Bulletin, 2000. The
Ministry of Public Works and Resettlement (MPWR), Vol. 2, No.13,
Ankara, Turkey.
[15] State Institute of Statistics (SIS), 2000. Construction Industry. Sector
Researches of Turkish Foundation Bank, 14pp, Ankara, Turkey.
[16] Zadeh L.A., 1965. "Fuzzysets". Information and Control, Vol: 8,
pp.338-352.
[17] Kaufmann, A., Gupta, M.M. 1985. Introduction to fuzzy Aritmetic,
Theory, and Applications, New York: Van Nostrand Reinhold C.
[18] Saito, T., Mukaidono, M., 1991. A Learning Algorithm for Max-Min
Network and Its Application to Solve Fuzzy Relation Equations. R.
Lowen and M. Roubens, eds.Proceedings, IFSA: 184-187.
[19] Dubois, D., Prade, H., 1980. Fuzzy Sets and Systems: Theory and
Applications, Vol: 144, Orlando, FLA: Academic Press.
[20] Zadeh, L.A., 1983. "The Role of Fuzzy Logic in The Management of
Uncertainty in Expert Systems", Fuzzy Sets and Syatems, Vol: 11,
pp.199-227.
[21] Bouchon-Meuner, B., 1992. "Inference With Imprecisions and
Uncertainties in Expert Systems", Fuzzy Expert Syatems, Vol: 2, pp.43-
54, FL: CRC Press.
[22] Kosko, B., 1986. "Fuzzy Knowledge Combination", International
Journal of Intelligent Systems, Vol: 1, pp.293-320.
[23] Yager, Y.Y., 1984. "General Multiple-Objective Functions and
Linguistically Quantified Statements", International Journal of Man-
Machine Studies, Vol: 21, pp.389-400.
[1] Tavakoli, A., Tulumen, S.C. 1990. "Construction Industry in Turkey".
Construction Management and Economics, Vol: 8, pp.77-87.
[2] Sanl─▒lar T. 1995. Quality Management in The Turkish Construction
Industry. M.Sc. Thesis, Boğaziçi University, Institute of Science,
132pp, Istanbul, Turkey
[3] Langford, D., Male, S., Strategic Management in Construction.
Blackwell Science, 250 pp., USA.
[4] Engineering News Record, 1994. Change in Bidding Law Could Aid
Turks Abroad, McGraw-Hill, pp. 27-8., New York.
[5] The Association of Turkish Construction Companies and Contractors
(ATCCC), 1995. Directory of Turkish Construction Contractors,
Ankara, Turkey.
[6] Erkut, H., 1992. "The Importance of Construction Industry in National
Economy and Effects of Construction Industry Management on
Economic Improvement". In: 3. ─░zmir Economy Congress, pp.91-103,
Izmir, Turkey.
[7] Engineering News Record, 1995. The Turkish Contractor - A Dynamic
Newcomer, pp. 1-12., New York.
[8] Yucel K. 1993. Cost of Rework in Construction for Maintaining Quality.
M.Sc. Thesis, Boğaziçi University, Institute of Science, 70pp, Istanbul,
Turkey
[9] Tur, R., 2003. Strategic Management of Construction Firms and Strategy
Formulation for The Sector. M.Sc. Thesis, Akdeniz University, Institute
of Science, 115pp, Antalya, Turkey
[10] Turkey-s Gazette, 2000. 2000 Planned Investments and Budget
Program, Ankara, Turkey.
[11] The Turkish Construction Catalog, 2003. The Turkish Society of Civil
Engineers (TSCE), Ankara, Turkey.
[12] The Central Bank of thr Republic of Turkey, 2003. "2003 Annual
Report", Ankara, Turkey.
[13] State Planning Organization (SPO), 1982. SPO Objects and Strategies
of Five Years Progress Plans. SPO Publications, 284pp, Ankara,
Turkey.
[14] The Ministry of Public Works and Resettlement-s Bulletin, 2000. The
Ministry of Public Works and Resettlement (MPWR), Vol. 2, No.13,
Ankara, Turkey.
[15] State Institute of Statistics (SIS), 2000. Construction Industry. Sector
Researches of Turkish Foundation Bank, 14pp, Ankara, Turkey.
[16] Zadeh L.A., 1965. "Fuzzysets". Information and Control, Vol: 8,
pp.338-352.
[17] Kaufmann, A., Gupta, M.M. 1985. Introduction to fuzzy Aritmetic,
Theory, and Applications, New York: Van Nostrand Reinhold C.
[18] Saito, T., Mukaidono, M., 1991. A Learning Algorithm for Max-Min
Network and Its Application to Solve Fuzzy Relation Equations. R.
Lowen and M. Roubens, eds.Proceedings, IFSA: 184-187.
[19] Dubois, D., Prade, H., 1980. Fuzzy Sets and Systems: Theory and
Applications, Vol: 144, Orlando, FLA: Academic Press.
[20] Zadeh, L.A., 1983. "The Role of Fuzzy Logic in The Management of
Uncertainty in Expert Systems", Fuzzy Sets and Syatems, Vol: 11,
pp.199-227.
[21] Bouchon-Meuner, B., 1992. "Inference With Imprecisions and
Uncertainties in Expert Systems", Fuzzy Expert Syatems, Vol: 2, pp.43-
54, FL: CRC Press.
[22] Kosko, B., 1986. "Fuzzy Knowledge Combination", International
Journal of Intelligent Systems, Vol: 1, pp.293-320.
[23] Yager, Y.Y., 1984. "General Multiple-Objective Functions and
Linguistically Quantified Statements", International Journal of Man-
Machine Studies, Vol: 21, pp.389-400.
@article{"International Journal of Architectural, Civil and Construction Sciences:51368", author = "R. Tur and A. Yardımcı", title = "A New Fuzzy Decision Support Method for Analysis of Economic Factors of Turkey's Construction Industry", abstract = "Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.
", keywords = "Fuzzy logic, decision support systems, construction industry.", volume = "1", number = "7", pages = "64-5", }
