Fuzzy Social Spider Optimization Algorithm for Fuzzy Clustering Analysis

Autor:	J. Revathi, P. Padmavathi, V. P. Eswaramurthy
Rok vydání:	2018
Předmět:	Fuzzy clustering Optimization algorithm biology Linear programming business.industry biology.organism_classification Fuzzy logic Replication (computing) ComputingMethodologies_PATTERNRECOGNITION Local optimum Artificial intelligence Cluster analysis business Social spider
Zdroj:	2018 International Conference on Current Trends towards Converging Technologies (ICCTCT).
DOI:	10.1109/icctct.2018.8550985
Popis:	Fuzzy clustering is a significant research problem in quite a lot of real time applications. Fuzzy C-Means (FCM) is a well-known prominent fuzzy clustering algorithm easily trapped in local optima. For solving local optima, recently, social spider optimization is use as a proposed model for solving global optima problem based on the replication of cooperative performance of social spiders. In this paper, the traditional social spider optimization algorithm is an integrated with fuzzy theory for solving clustering problem which is refer to fuzzy social spider optimization (FSSO). The experimental result shows that the proposed fuzzy social spider optimization clustering algorithms reveal better performance for solving clustering problems.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::58087ca1044ed9b4b4ce8869d8c32cc4 https://doi.org/10.1109/icctct.2018.8550985 Zobrazit plný text záznamu