Nowcasting Various Forms of Precipitation Using Improvised Random Forest Classifier

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Author(s): Ashritha Pilly (Osmania, India)and C. Kishor Kumar Reddy (Stanley College of Engineering and Technology for Women, India)
Copyright: 2024
Pages: 22
Source title: Advanced Geospatial Practices in Natural Environment Resource Management
Source Author(s)/Editor(s): Rubeena Vohra (Bharati Vidyapeeth's College of Engineering, India)and Ashish Kumar (Bennett University, India)
DOI: 10.4018/979-8-3693-1396-1.ch005

Keywords: Environment & Agriculture / Geographic Information Systems / Information Science Reference / Natural Resource Management

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Abstract

Weather forecasting is the utilization of science and technology to foresee the conditions of the atmosphere for a given location and time. Weather forecasting is high priority since it helps to settle future climate changes and provides information on critical weather conditions. As the weather has a great impact on various aspects of human life, aquatic life, aviation industry, and others, efforts have been made for decades to improve the efficiency of weather forecasting to ensure a better life and to reduce economic loss, but the result is not more precise than expected. The present research focuses on improving the efficiency of weather forecasting, focusing on various forms of precipitation such as rain, snow, hailstorms, and snowflakes by making use of historical numerical weather datasets across the globe. The efficiency in terms of performance measures has been compared with existing models.

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Nowcasting Various Forms of Precipitation Using Improvised Random Forest Classifier

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