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    ARTICLE

    Machine Learning-Based Threatened Species Translocation Under Climate Vulnerability

    Nandhi Kesavan*, Latha

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 327-337, 2023, DOI:10.32604/iasc.2023.030910 - 29 September 2022

    Abstract Climate change is the most serious causes and has a direct impact on biodiversity. According to the world’s biodiversity conservation organization, reptile species are most affected since their biological and ecological qualities are directly linked to climate. Due to a lack of time frame in existing works, conservation adoption affects the performance of existing works. The proposed research presents a knowledge-driven Decision Support System (DSS) including the assisted translocation to adapt to future climate change to conserving from its extinction. The Dynamic approach is used to develop a knowledge-driven DSS using machine learning by applying More >

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