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Transformative Synergy: Machine Learning and Neural Networks in Environmental Science

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Asian Journal of Basic and Applied Sciences, 2024


  • Betania Rahayu


This article explores the symbiotic relationship between machine learning, neural networks, and environmental science, aiming to harness the power of advanced technologies to address pressing environmental challenges. The research investigates how machine learning algorithms and neural networks can be applied to analyze complex environmental data, model intricate ecological systems, and contribute to sustainable solutions. Through an extensive literature review, a robust research methodology, and a presentation of results, this study delves into the transformative potential of integrating machine learning and neural networks in the realm of environmental science.

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