An attempt to use the KEEL tool to evaluate fuzzy models for real estate appraisal

Frontiers in Artificial Intelligence and Applications

Volumn 181, Issue 1, 2008, Pages 125-139

  Lasota, Tadeusz ^a   Trawiński, Bogdan ^b   Trawiński, Krzysztof ^b  

^a WROC AW UNIVERSITY OF ENVIRONMENTAL AND LIFE SCIENCES   (Poland)

^b WROCLAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

cadastral system; genetic fuzzy system; KEEL; real estate appraisal

Indexed keywords

FUZZY INFERENCE;

CADASTRAL SYSTEM; FUZZY MODELING; GENETIC FUZZY SYSTEMS; GENETIC FUZZY-SYSTEM; INPUT VARIABLES; KEEL; PROPERTY; REAL ESTATE APPRAISALS; REGRESSION ALGORITHMS; RESEARCH CENTER;

DATA HANDLING;

EID: 84875963393     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: 10.3233/978-1-58603-904-2-125     Document Type: Article

References (27)

1. J. Alcala-Fdez, L. Sanchez, S. Garca, M.J. del Jesus, S. Ventura, J.M. Garrell, J. Otero, C. Romero, J. Bacardit, V.M. Rivas, J.C. Fernandez, F. Herrera, KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems, 2008, http://www.keel.es/(to be published in Soft Computing).
2. J. Alcala-Fdez, S. Garca, F.J. Berlanga, A. Fernandez, L. Sanchez, M.J. del Jesus, F. Herrera, KEEL: A data mining software tool integrating genetic fuzzy systems. Proceedings of the 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS'08), F. Hoffmann et al., eds, IEEE, Piscataway, NJ, 2008, 83-88.
3. M. d'Amato, Comparing Rough Set Theory with Multiple Regression Analysis as Automated Valuation Methodologies, International Real Estate Review 10(2) (2007), 42-65.
4. C. Bagnoli, H. C. Smith, The Theory of Fuzzy Logic and its Application to Real Estate Valuation, Journal of Real Estate Research 16(2) (1998), 169-199.
5. P. P. Bonissone, W. Cheetham, Financial Applications of Fuzzy Case-Based Reasoning to Residential Property Valuation, In Proc. of the 6th IEEE International Conference on Fuzzy Systems, Barcelona, 1997, 37-44.
6. B. Carse, T.C. Fogarty, A. Munro, Evolving fuzzy rule based controllers using genetic algorithms, Fuzzy Sets and Systems 80:3 (1996) 273-293.
7. J. Casillas, O. Cordón, F. Herrera, COR: A methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules, IEEE Transactions on System, Man and Cybernetics, Part B: Cybernetics 32:4 (2002) 526-537.
8. G.H Castle, GIS: Meeting the Information Demand, Valuation Insights and Real Estate Investor 42(1) (1998) 66-71.
9. W.J. McCluskey, S. Anand: The application of intelligent hybrid techniques for the mass appraisal of residential properties, Journal of Property Investment and Finance, Vol.17, No.3, (1999) 218-239.
10. Q. Do, G. Grudnitski: A Neural Network Approach to Residential Property Appraisal. Real Estate Appraiser, December 1992, 38-45.
11. M.A.S. González C.T. Formoso: Mass appraisal with genetic fuzzy rule-based systems, Property Management 24(1) (2006), 20-30.
12. A. Homaifar, E. McCormick: Simultaneous Design of Membership Functions and Rule Sets for Fuzzy Controllers Using Genetic Algorithms, IEEE Transactions on Fuzzy Systems 3:2 (1995) 129-139.
13. D. Król, T. Lasota, W. Nalepa, and B. Trawiski: Fuzzy system model to assist with real estate appraisals, Lecture Notes in Artificial Intelligence 4570, 2007, 260-269.
14. D. Król, T. Lasota, B. Trawiski, and K. Trawiski: Comparison of Mamdani and TSK Fuzzy Models for Real Estate Appraisal, Lecture Notes in Artificial Intelligence 4693, 2007, 1008-1015.
15. D. Król, T. Lasota, B. Trawiski, and K. Trawiski: Investigation of evolutionary optimization methods of TSK Fuzzy Model for Real Estate Appraisal, International Journal of Hybrid Intelligent Systems 5 (2008) 1-18.
16. T. Lasota, B. Trawiski, and K. Trawiski: Evolutionary Generation of Rule Base in TSK Fuzzy Model for Real Estate Appraisal, Proceedings of the 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS'08), F. Hoffmann et al., eds, IEEE, Piscataway, NJ, 2008, 71-76.
17. T. Lasota, B. Trawiski, and K. Trawiski: Evolutionary Optimization of TSK Fuzzy Model to Assist with Real Estate Appraisals, in Computational Intelligence: Methods and Applications, L. Rutkowski, R. Tadeusiewicz, L.A. Zadeh and J. Zurada, eds, EXIT, Warszawa, 2008, 232-243.
18. N. Nguyen, A. Cripps: Predicting housing value: A comparison of multiple regression analysis and artificial neural networks, Journal of Real Estate Research 22(3) (2001), 3131-3336.
19. L. Sánchez,: A Random Sets-Based Method for Identifying Fuzzy Models, Fuzzy Sets and Systems 98:3 (1998) 343-354.
20. L. Soibelman, M.A.S. González: A Knowledge Discovery in Databases Framework for Property Valuation, Journal of Property Tax Assessment and Administration, Vol. 7, No. 2, (2002) 77-106.
21. M. Sygnowski, B. Trawiski, and A. Zgrzywa,: An Attempt to Use a Type-2 Fuzzy Logic System to Assist with Real Estate Appraisals, Proceedings of the 1st International Conference on Information Technology (IT 2008), A. Stepnowski et al., eds, IEEE, Piscataway, NJ, 2008, pp. 189-192.
22. W.Z. Taffese,: Case-based reasoning and neural networks for real state valuation, Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications, Innsbruck, Austria (2007).
23. P. Thrift: Fuzzy logic synthesis with genetic algorithms, Proceedings of 4th International Conference on Genetic Algorithms (ICGA'91), pp 509-513.
24. B.D. Waller, T.H. Greer, N.F. Riley: An Appraisal Tool for the 21st Century: Automated Valuation Models, Australian Property Journal Vol. 36 No. 7 (2001) 636-641.
25. L.X. Wang, J.M. Mendel: Generating Fuzzy Rules by Learning from Examples, IEEE Transactions on Systems, Man and Cybernetics 22:6 (1992) 1414-1427.
26. E. Worzala, M. Lenk, A. Silva: An Exploration of Neural Networks and Its Application to Real Estate Valuation, The Journal of Real Estate Research 10(2) (1995), 185-201.
27. P. Wyatt: The development of a GIS-based property information system for real estate valuation, International Journal of Geographical Information Science, Vol. 111, No. 5 (1997) 435-450.