Application of Machine Learning in Climate Change Strategies

This research work aims to explore the integration of artificial intelligence technologies to improve climate change adaptation strategies. Research focuses on the development of AI-based risk assessment models that can analyze multidimensional data, including environmental factors, socio-economic variables and infrastructure vulnerability. These models employ machine learning algorithms to pinpoint high-risk regions and populations that are susceptible to climate change’s effects, including temperature swings, sea level rise, and extreme weather. In addition, the paper explores the development of AI-based decision support systems (DSS) to help policy makers, urban planners and stakeholders develop effective adaptation plans and allocate resources efficiently. Case studies and simulations are used to assess the effectiveness of AI-based risk assessment and DSS in improving climate change resilience and promoting sustainability in vulnerable regions. In summary, this research aims to advance the development of artificial intelligence-based solutions for climate change adaptation and mitigation.