An Economic Approach to Predict Biomass Level of Bangladesh Sundarbans Region Using Fuzzy Inference System

Kanisha Pujaru (), Soovoojeet Jana, Anupam Khatua, Sayani Adak () and T. K. Kar ()
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Kanisha Pujaru: Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Botanic Garden, Howrah 711103, West Bengal, India
Soovoojeet Jana: ��Department of Mathematics, Ramsaday College, Amta, Howrah 711401, West Bengal, India
Anupam Khatua: Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Botanic Garden, Howrah 711103, West Bengal, India‡Department of Applied Sciences and Humanities, National Institute of Advanced Manufacturing, Technology, Ranchi, Jharkhand 834003, India
Sayani Adak: Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Botanic Garden, Howrah 711103, West Bengal, India
T. K. Kar: Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Botanic Garden, Howrah 711103, West Bengal, India

New Mathematics and Natural Computation (NMNC), 2023, vol. 19, issue 03, 737-755

Abstract: Seas, marine, and coastal regions are integral and essential parts of our ecosystem. Many scientific approaches have been taken to ensure the sustainable use of marine resources. Artificial intelligence (AI) plays a vital role in harvesting resources so that the system regenerates itself for the long term. This paper develops a two-input and two-output fuzzy logic-based model to predict the fisheries’ remaining biomass after harvesting and maintaining a high revenue level in the Bangladesh Sundarbans region. Fishing & tourism are taken as input parameters, and revenue & biomass are taken as output parameters. A total of 20 rules (IF-THEN type) have been generated in the fuzzy rule editor of Fuzzy Inference System (FIS), considering all possible combinations between input–output parameters. The data which we obtained from the real ecosystem exactly corresponds to the results that we got from our proposed model. Our fuzzy logic model yields valid predictions of the remaining biomass level without compromising profit, only by controlling the harvesting and tourist entry.

Keywords: Fuzzy logic; fishing; tourism; biomass; revenue; artificial intelligence (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S1793005723500321

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