Application of fuzzy system theory in addressing the presence of uncertainties

Yusmye, A. Y. N.; Goh, B. Y.; Adnan, N. F.; Ariffin, A. K.

doi:10.1063/1.4907518

Title: Application of fuzzy system theory in addressing the presence of uncertainties

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Abstract

In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from themore »« less

Authors:

Yusmye, A. Y. N. ^[1]; Goh, B. Y.; Adnan, N. F.; Ariffin, A. K. ^[2]

Institute of Engineering Mathematics, Universiti Malaysia Perlis Kampus Pauh Putra, 02600, Arau, Perlis (Malaysia)
Department of Mechanical and Materials, Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia 43600 UKM Bangi, Selangor (Malaysia)

Publication Date:: Tue Feb 03 00:00:00 EST 2015

OSTI Identifier:: 22390953

Resource Type:: Journal Article

Journal Name:: AIP Conference Proceedings

Additional Journal Information:: Journal Volume: 1643; Journal Issue: 1; Conference: 2. ISM International Statistical Conference 2014: Empowering the Applications of Statistical and Mathematical Sciences, Pahang (Malaysia), 12-14 Aug 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-243X

Country of Publication:: United States

Language:: English

Subject:: 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; COMPARATIVE EVALUATIONS; COMPUTERIZED SIMULATION; CONVERSION; ERRORS; FAILURES; FINITE ELEMENT METHOD; FUZZY LOGIC; MAPPING; PROBABILISTIC ESTIMATION; STOCHASTIC PROCESSES

Citation Formats


                    Yusmye, A. Y. N., Goh, B. Y., Adnan, N. F., and Ariffin, A. K. Application of fuzzy system theory in addressing the presence of uncertainties.  United States: N. p., 2015. 
        Web.  doi:10.1063/1.4907518.

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                    Yusmye, A. Y. N., Goh, B. Y., Adnan, N. F., & Ariffin, A. K. Application of fuzzy system theory in addressing the presence of uncertainties.  United States.  https://doi.org/10.1063/1.4907518

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                    Yusmye, A. Y. N., Goh, B. Y., Adnan, N. F., and Ariffin, A. K. 2015.  
        "Application of fuzzy system theory in addressing the presence of uncertainties".  United States.  https://doi.org/10.1063/1.4907518.

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@article{osti_22390953,

  title        = {Application of fuzzy system theory in addressing the presence of uncertainties},

  author       = {Yusmye, A. Y. N. and Goh, B. Y. and Adnan, N. F. and Ariffin, A. K.},

  abstractNote = {In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.},

  doi          = {10.1063/1.4907518},

  url          = {https://www.osti.gov/biblio/22390953},
  journal      = {AIP Conference Proceedings},

  issn         = {0094-243X},

  number       = 1,

  volume       = 1643,

  place        = {United States},

  year         = {Tue Feb 03 00:00:00 EST 2015},

  month        = {Tue Feb 03 00:00:00 EST 2015}

}

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