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Leveraging Fuzzy Logic for Habitat Suitability Analysis: A Comprehensive Case Study in Digital Ecosystems |
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PP: 335-347 |
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doi:10.18576/amis/190210
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Author(s) |
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Suleiman Ibrahim Mohammad,
N. Yogeesh,
N. Raja,
R. Chetana,
M. S. Ramesha,
Asokan Vasudevan,
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Abstract |
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| Digital Nature or the virtual representation of natural environments is an emerging object of study in ecology due to its usefulness to simulate complex ecological processes and contribute to the planning of conservations. But, when uncertainty and complexity that characterize ecological processes complicate accurate modelling and estimating habitat suitability in Digital Nature. We present a fuzzy logic based new methodology in this research for uncertainty in habitat suitability in Digital Nature. One case study utilizes fuzzy logic to model ecological processes and assess habitat suitability for a target species. The uncertainties involved in ecological variables were represented by fuzzy membership functions, fuzzy rules and fuzzy inference systems. Based on the analysis of the case study, it is clear that the fuzzy logic-based approach is effective in dealing with uncertainties and takes the results of the habitat suitability assessment a step further into nuance and interpretability. This study makes an additional contribution to the expanding body of literature on Digital Nature and fuzzy logic in ecological modelling, offering further insights into conservation planning and decision-making in virtual settings. Why it also needs to be researched to help with fuzzy logic potentiality in respective Digital Nature applications and the concept can be tweaked further based on ecological variations.
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