Prediction of Sunspots using Fuzzy Logic: A Triangular Membership Function-based Fuzzy C-Means Approach

Abstract: Fuzzy logic is an algorithm that works on “degree of truth”, instead of the conventional crisp logic where the possible answer can be 1 or 0. Fuzzy logic resembles human thinking as it considers all the possible outcomes between 1 and 0 and it tries to reflect reality. Generation of membership functions is the key factor of fuzzy logic. An approach for generating fuzzy gaussian and triangular membership function using fuzzy c-means is considered in this research. The problem related to sunspot prediction is considered and its accuracy is calculated. It is evident from the results that the proposed technique of generating membership functions using fuzzy c-means can be adopted for predicting sunspots.

Muhammad Hamza Azam, Mohd Hilmi Hasan, Said Jadid Abdul Kadir and Saima Hassan. “Prediction of Sunspots using Fuzzy Logic: A Triangular Membership Function-based Fuzzy C-Means Approach”. International Journal of Advanced Computer Science and Applications (IJACSA) 12.2 (2021). http://dx.doi.org/10.14569/IJACSA.2021.0120245

@article{Azam2021,
title = {Prediction of Sunspots using Fuzzy Logic: A Triangular Membership Function-based Fuzzy C-Means Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120245},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120245},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {2},
author = {Muhammad Hamza Azam and Mohd Hilmi Hasan and Said Jadid Abdul Kadir and Saima Hassan}
}