Applications of Fuzzy Technology in Business Intelligence


  • Andreas Meyer INFORM Institut f. Operations Research und Management GmbH Risk & Fraud Division Pascalstr. 23 52076 Aachen, Germany
  • Hans-Jí¼rgen Zimmermann RWTH, Aachen Institute of Technology Templer Graben 55 52062 Aachen, Germany


fuzzy technology in business intelligence, fraud detection, risk assessment, intelligent data mining, fuzzy expert systems


Fuzzy Set Theory has been developed during the last decades to a demanding mathematical theory. There exist more than 50,000 publications in this area by now. Unluckily the number of reports on applications of fuzzy technology has become very scarce. The reasons for that are manifold: Real applications are normally not single-method-applications but rather complex combinations of different techniques, which are not suited for a publication in a journal. Sometimes considerations of competition my play a role, and sometimes the theoretical core of an application is not suited for publication. In this paper we shall focus on applications of fuzzy technology on real problems in business management. Two versions of fuzzy technology will be used: Fuzzy Knowledge based systems and fuzzy clustering. It is assumed that the reader is familiar with basic fuzzy set theory and the goal of the paper is, to show that the potential of applying fuzzy technology in management is still very large and hardly exploited so far.


L. Angstenberger, Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering, Kluwer Academic Publishers, Boston, Dodrecht, London, 2001

J.C. Bezdek, Pattern Recognition with fuzzy objective function algorithms, New York, London, 1981

J.C. Bezdek, J.D. Harris, Fuzzy partitions and relations, Fuzzy Sets and Systems 1, 111-127, 1978

B.Bouchon-Meunier, R.R.Yager, L.A.Zadeh (edtrs.) Uncertainty in Intelligent and Information Systems, World Scientific, Singapore, 2000

H. Dishkant, About membership function estimation, Fuzzy Sets and Systems 5, pp.141-147, 1981

D. Dubois, H. Prade, A review of fuzzy set aggregation connectives, Information Science 36, pp.85-121, 1985

Ch. Freksa, Linguistic description of human judgments in expert systems and in the soft sciences, in: M.M. Gupta, E. Sanchez (edtrs), Approximate Reasoning in Decision Analysis, Amsterdam, New York, Oxford, 1982

J.M. Hammerbacher, R.R Yager, The personalization of security:An application of fuzzy set theory, Fuzzy Sets and Systems 5, pp. 1-9, 1981

H.M. Hersh, A. Caramazza, H.H. Brownell, Effects of context on fuzzy membership functions, in:M.M. Gupta et al.(edtrs) Advances in Fuzzy Set Theory and Applications, Amsterdam, New York, Oxford, 1979

INFORM, fuzzyTECH 5.8, User Manual, available via, Aachen, 2010

INFORM, RiskShield 4.0, User Manual, available via, Aachen, 2011

R.Krishnapuram, J.M.Keller, A possibilistic approach to clustering, IEEE Trans. Fuzzy Systmes 1, 98-110, 1993

E.H. Mamdani, Application of fuzzy logic to approximate reasoning, IEEE Trans.Comput. 26, pp. 1182-1191, 1977

MIT DataEngine Manual 2.1, MIT GmbH, Aachen, 1997

M. Mizumoto, H.-J. Zimmermann, Comparison of fuzzy reasoning methods, Fuzzy Sets and Systems,8, pp.253-283, 1982

A.M. Norwich, L.B. Turksen, A model for the measurement of membership and consequences of its empirical implementation, Fuzzy Sets and Systems 12, pp.1-25, 1984

D. Ruan, A critical study of widely used fuzzy implication operators and the inference rules in fuzzy expert systems, Ph.D. Thesis, Gent 1990

A.Salski, Ecological Modeling and Data Analysis, in: H.-J. Zimmermann (edtr.): Practical Applications of Fuzzy Technologies, Kluwer Academic Publ., Boston 1999, pp.247-266

U. Thole, H.-J. Zimmermann, P. Zysno, On the suitability of minimum and product operators for the intersection of fuzzy sets, Fuzzy Sets and Systems 2, pp.167-180, 1979

L.A. Zadeh, Fuzzy Sets, Information and Control 8, pp.338-353, 1965

L.A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning, Memorandum ERL-M 411, Berkeley 1973

L.A. Zadeh, Outline of a new approach to the analysis of complex systems and decision processes, IEEE Trans.Syst.Man Cybernet. 3, pp. 28-44, 1973

L.A. Zadeh, The role of fuzzy logic in the management of uncertainty in expert systems, Fuzzy Sets and Systems 11, 199-227, 1983

L.A. Zadeh, A New Frontier in Computation - Computation with Information Described in Natural Language, in: From Natural Language to Soft Computing: New Paradigms in Artificial Intelligence .L.A.Zadeh, Dan Tufis, F.G.Filip, I.Dzitac (Edtrs), Editura Academiei Romane, Bäile Felix (Rom.), 2008

H.-J. Zimmermann, Testability and meaning of mathematical models in social sciences, Mathematical Modelling 1, pp.123-139, 1980

H.-J. Zimmermann, Fuzzy Sets, Decision Making, and Expert Systems, Kluwer, Boston, Dodrecht, Lancaster, 1987

H.-J. Zimmermann, Fuzzy set theory - and inference mechanism, in: G.Mitra (edr.) Mathematical models for decision support, Berlin , Heidelberg 1988

H.-J. Zimmermann, P.Zysno, Latent connectives in human decision making, Fuzzy Sets and Systems 4, pp.37-51, 1980

H.-J. Zimmermann, P. Zysno, Decisions and evaluations by hierarchical aggregation of information, Fuzzy Sets and Systems 10, pp.243-266, 1983

H.-J. Zimmermann, Fuzzy Set Theory and its Applications, fourth edition, Boston, Dodrecht, London, 2001



Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.