Araştırma Makalesi

Fuzzy inverse logic: part-2. validation and evaluation of the method

Cilt: 11 Sayı: 3 15 Temmuz 2021
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Fuzzy inverse logic: part-2. validation and evaluation of the method

Abstract

In the first part of this study, which consists of two parts, the introduction of the fuzzy inverse logic method, its foundations, computation and process flow and details were given. In this second part, the method was applied on a very simple mathematical problem and on a simple civil engineering design problem in order to investigate and evaluate the validity of the method easily. Fuzzy inverse logic computations have been carried out on these two simple problems for different dimension, sensitivity and acceptable error values. By comparing the obtained results with the desired outputs and mathematical results, the effective computation ability of the method was tried to be revealed. As a result, it is understood that the method developed in this study has many promising aspects in terms of theoretical computations and practical applications and can be used effectively in many scientific fields.

Keywords

Artificial intelligence , Design , Engineering , Fuzzy logic , Fuzzy reverse logic , Logic

Kaynakça

  1. Altaş, İ. H. (1999a). Bulanık Mantık: Bulanıklılık Kavramı. Enerji, Elektrik, Elektromekanik-3e,62, 80-85.
  2. Altaş, İ. H. (1999b). Bulanık mantık: Bulanık denetim. Enerji, Elektrik, Elektromekanik-3e, 64(1999), 76-81.
  3. Altaş, I. H. (2017). Fuzzy Logic Control in Energy Systems with Design Applications in MATLAB®/Simulink® (91). IET.
  4. Chopard, B. and Droz, M. (1998). Cellular automata (Vol. 1). Berlin, Germany: Springer.
  5. Cvijović, D. and Klinowski, J. (1995). Taboo search: an approach to the multiple minima problem. Science, 267 (5198), 664-666. https://doi.org/10.1126/science.267.5198.664
  6. Erdun, H. (2020). Fuzzy Logic Defuzzification (Bulanıklaştırma) Methods with Examples: Erişim adresi https://www.researchgate.net/publication/344196954_Fuzzy_Logic_Defuzzification_Bulaniklastirma_Methods_with_Examples
  7. Harris, J. (2005). Fuzzy logic applications in engineering science (Vol. 29). Springer Science & Business Media.
  8. Jain, A. K., Mao, J. and Mohiuddin, K. M. (1996). Artificial neural networks: A tutorial. Computer, 29(3), 31-44. https://doi.org/10.1109/2.485891
  9. Kennedy, J. and Eberhart, R. (1995). Particle swarm optimization. In Proceedings of ICNN'95-international conference on neural networks, 4, 1942-1948.
  10. Karaboga, D. and Akay, B. (2009). A comparative study of artificial bee colony algorithm. Applied mathematics and computation, 214(1), 108-132. https://doi.org/10.1016/j.amc.2009.03.090

Kaynak Göster

APA
Öztekin, E. (2021). Fuzzy inverse logic: part-2. validation and evaluation of the method. Gümüşhane Üniversitesi Fen Bilimleri Dergisi, 11(3), 768-791. https://doi.org/10.17714/gumusfenbil.894879