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

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 funct...

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Bibliographic Details
Published inInternational journal of advanced computer science & applications Vol. 12; no. 2
Main Authors Azam, Muhammad Hamza, Hilmi, Mohd, Jadid, Said, Hassan, Saima
Format Journal Article
LanguageEnglish
Published West Yorkshire Science and Information (SAI) Organization Limited 2021
Subjects
Algorithms
Fuzzy logic
Sunspots
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Summary: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.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2021.0120245