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2023, Vol. 8, Issue 2, Part A

Fuzzy combined effect time quantity dependent data matrix for predicting phytal fauna distribution and diversity


Author(s): Azhagu Raj R, Patrick F, Babisha Julit RL and Divvyanadam I

Abstract: Fuzzy logic can be used to analyse and classify flora and faunal diversity. It uses fuzzy logic to describe richness and complexity of plant and animal life. Fuzzy logic can identify patterns in data to better understand diversity of an ecosystem. This study used a fuzzy combined effect time quantity dependent data matrix to predict the distribution and diversity of phytal fauna in Erayumanthurai coast. The method involved the use of Initial Raw Data Matrix (IRDM), Average Quantity Dependent Data Matrix (AQDM), Refined Quantity Dependent Data Matrices (RQDMs) and Combined Effect Quantity Dependent Data Matrix (CEQDM). Results showed that the high number of fauna was recorded in sites at α = 0.75 level and the faunal ranges were medium at α = 0.5 level. Negative values in the sites of S2, S3, and S4 indicated that faunal composition in these sites was not preferred. This fuzzy combined effect time quantity dependent data matrix was able to predict the exact place that had more anthropogenic disturbance to disturb the diversity and distribution of phytal fauna.

DOI: 10.22271/maths.2023.v8.i2a.939

Pages: 09-12 | Views: 254 | Downloads: 28

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How to cite this article:
Azhagu Raj R, Patrick F, Babisha Julit RL, Divvyanadam I. Fuzzy combined effect time quantity dependent data matrix for predicting phytal fauna distribution and diversity. Int J Stat Appl Math 2023;8(2):09-12. DOI: 10.22271/maths.2023.v8.i2a.939
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