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Utilizing Machine Learning for Enhanced Weather Forecasting and Sustainable Water Resource Management
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Author(s): Risha Dhargalkar (Government College Sanquelim, Goa University, India), Viosha Cruz (Carmel College of Arts Science and Commerce, India)and Abdullah Alzahrani (Oakland University, USA)
Copyright: 2024
Pages: 17
Source title:
Innovations in Machine Learning and IoT for Water Management
Source Author(s)/Editor(s): Abhishek Kumar (Chandigarh University, India), Arun Lal Srivastav (Chitkara University, India), Ashutosh Kumar Dubey (University of Castilla-La Mancha, Spain), Vishal Dutt (AVN Innovations Pvt. Ltd., India)and Narayan Vyas (AVN Innovations Pvt. Ltd., India)
DOI: 10.4018/979-8-3693-1194-3.ch006
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Abstract
Every phase of human life is influenced by nature; therefore, weather forecasting and water management are challenging tasks as they work according to environmental changes. The traditional weather forecasting model was done using historical data in a physics model, which leads to unsteady results. With machine learning and artificial intelligence advancement, weather forecasting and water management have undergone revolutions to predict future data analysis. This chapter provides an overview of essential weather forecasting attributes and different data acquisition and preprocessing elements in water management. The chapter's subsequent sections detail the many stages needed for weather forecasting and the various machine-learning algorithms that may be used to forecast weather conditions by recognizing patterns and then analyzing them. In addition to this, the chapter also highlights applications of water resource management. Since water is a vital resource, automation and controlling allocation and distribution are crucial tasks, which are also outlined.
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