4.6 Article

A Novel Fuzzy System With Adaptive Neurons for Earthquake Modeling

Journal

IEEE ACCESS
Volume 8, Issue -, Pages 101369-101376

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2998446

Keywords

Fuzzy system; neural networks; earthquake modeling; stability

Funding

  1. CONACYT Postdoctoral Scholarship
  2. CONACYT Basic Science [A1-S-8216]
  3. CONACYT Research Fellows Program

Ask authors/readers for more resources

Data driven fuzzy neural networks have some disadvantages, such as high dimensions and complex learning process. Also, the obtained models are difficult to interpret. In this paper, we propose a novel simple fuzzy system, which uses fuzzy adaptive neurons. This novel model takes the advantages of the interpretability of the fuzzy system and good approximation ability of the neural networks. We propose a simple learning algorithm for the novel fuzzy system. The stability analysis is given. We successfully apply this fuzzy model for the earthquake modeling. Comparisons with the popular fuzzy neural model are proposed.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available