The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Fuzzy logic systems for engineering: a tutorial
Abstract
A fuzzy logic system (FLS) is unique in that it is able to simultaneously handle numerical data and linguistic knowledge. It is a nonlinear mapping of an input data (feature) vector into a scalar output, i.e., it maps numbers into numbers. Fuzzy set theory and fuzzy logic establish the specifics of the nonlinear mapping. This tutorial paper provides a guided tour through those aspects of fuzzy sets and fuzzy logic that are necessary to synthesize an FLS. It does this by starting with crisp set theory and dual logic and demonstrating how both can be extended to their fuzzy counterparts. Because engineering systems are, for the most part, causal, we impose causality as a constraint on the development of the FLS. After synthesizing a FLS, we demonstrate that it can be expressed mathematically as a linear combination of fuzzy basis functions, and is a nonlinear universal function approximator, a property that it shares with feedforward neural networks. The fuzzy basis function expansion is very powerful because its basis functions can be derived from either numerical data or linguistic knowledge, both of which can be cast into the forms of IF-THEN rules.>
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Cites
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Multilayer feedforward networks are universal approximators
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Approximation by superpositions of a sigmoidal function
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Multilayer feedforward networks are universal approximators
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Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
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Cited by
Karnik, N. N., Mendel, J. M., & Liang, Q. (1999) · IEEE Transactions on Fuzzy Systems · doi:10.1109/91.811231 · Cited by 1,643
Self-citationColchester, K., Hagras, H., Alghazzawi, D., & Aldabbagh, G. (2017) · Journal of Artificial Intelligence and Soft Computing Research · doi:10.1515/jaiscr-2017-0004 · Cited by 328
The 2017 IEEE International Conference on Fuzzy Systems
(2016) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2016.2545826 · Cited by 308
Generative AI design for building structures
Liao, W., Lu, X., Fei, Y., Gu, Y., & Huang, Y. (2024) · Automation in Construction · doi:10.1016/j.autcon.2023.105187 · Cited by 213
Fuzzy FMEA application to improve purchasing process in a public hospital
Kumru, M., & Kumru, P. Y. (2013) · Applied Soft Computing · doi:10.1016/j.asoc.2012.08.007 · Cited by 207
Metadata
- Authors
- Mendel, J. M.
- Venue
- Proceedings of the IEEE
- Published
- 1995-03
- Volume
- 83
- Issue
- 3
- Pages
- 345-377
- ISSN
- 0018-9219 (ISSN-L)
- OpenAlex
- W2032521963
- Cited by
- 2,110
- References
- 59
- FWCI
- 41.17
- Type
- journal article
- Language
- en
- Open access
- closed
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