Öz
A note on the information-theoretic aspect of the fuzzy neural tree (FNT) is presented. The detailed description of the FNT is given in an earlier work, where its information-theoretic aspect is heuristically mentioned but not elaborated because of some space limitation. The present note is to highlight this aspect of the tree as this is important in working of the tree with its knowledge-driven structure.
Anahtar Kelimeler
Fuzzy logic neural tree knowledge modeling evolutionary computation likelihood probability possibility
Kaynakça
- [1] Ö. Ciftcioglu and M. S. Bittermann, "A Fuzzy Neural Tree Based on Likelihood," presented at the 2015 IEEE International Conference on Fuzzy Systems - FUZZ-IEEE 2015, Istanbul, Turkey, 2015.
- [2] D. Dubois and H. Prade, "A semantics for possibility theory based on likelihoods," J. of Mathematical Analysis and Applications pp. 205, 359- 380, 1997.
- [3] D. Dubois and H. Prade, "A semantics for possibility theory based on likelihoods," in Int. Joint Conf. of Fourth IEEE Int. Conf. on Fuzzy Systems and Second Int. Fuzzy Engineering Symposium - Fuzzy Systems 1995, Yokohama, Japan, 1995, pp. 1597-1604.
- [4] A. Papoulis, Probability, Random Variables and Stochastic Processes. New York: McGraw-Hill, 1965.
- [5] Y. Pawitan, In All Likelihood: Statistical Modelling and Inference Using Likelihood. New York: Clarendon Press Oxford, 2001.
- [6] L. A. Zadeh, "Is there a need for fuzzy logic?," Information Sciences, vol. 178, pp. 2751-2779, 2008.
- [7] Ö. Ciftcioglu and M. S. Bittermann, "Computational Cognitive Color Perception," presented at the IEEE World Congress on Computational Intelligence - WCCI 2016, Vancouver, Canada, 2016.
- [8] O. Ciftcioglu and M. S. Bittermann, "Fuzzy Neural Tree in Evolutionary Computation for Architectural Design Cognition," in IEEE Congress on Evolutionary Computation - CEC 2015, Sendai, Japan, 2015, pp. 2319 -2326.
Öz
Kaynakça
- [1] Ö. Ciftcioglu and M. S. Bittermann, "A Fuzzy Neural Tree Based on Likelihood," presented at the 2015 IEEE International Conference on Fuzzy Systems - FUZZ-IEEE 2015, Istanbul, Turkey, 2015.
- [2] D. Dubois and H. Prade, "A semantics for possibility theory based on likelihoods," J. of Mathematical Analysis and Applications pp. 205, 359- 380, 1997.
- [3] D. Dubois and H. Prade, "A semantics for possibility theory based on likelihoods," in Int. Joint Conf. of Fourth IEEE Int. Conf. on Fuzzy Systems and Second Int. Fuzzy Engineering Symposium - Fuzzy Systems 1995, Yokohama, Japan, 1995, pp. 1597-1604.
- [4] A. Papoulis, Probability, Random Variables and Stochastic Processes. New York: McGraw-Hill, 1965.
- [5] Y. Pawitan, In All Likelihood: Statistical Modelling and Inference Using Likelihood. New York: Clarendon Press Oxford, 2001.
- [6] L. A. Zadeh, "Is there a need for fuzzy logic?," Information Sciences, vol. 178, pp. 2751-2779, 2008.
- [7] Ö. Ciftcioglu and M. S. Bittermann, "Computational Cognitive Color Perception," presented at the IEEE World Congress on Computational Intelligence - WCCI 2016, Vancouver, Canada, 2016.
- [8] O. Ciftcioglu and M. S. Bittermann, "Fuzzy Neural Tree in Evolutionary Computation for Architectural Design Cognition," in IEEE Congress on Evolutionary Computation - CEC 2015, Sendai, Japan, 2015, pp. 2319 -2326.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Elektrik Mühendisliği |
| Bölüm | Articles |
| Yazarlar | |
| Yayımlanma Tarihi | 30 Aralık 2016 |
| Yayımlandığı Sayı | Yıl 2016 Cilt: 1 Sayı: 1 |
