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 under high priority since it helps to settle future climate changes and provide 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 much precise than expected. The present research focuses on improving the efficiency of weather forecasting, focusing on various forms of precipitation such as rain, snow, hail storms, 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.
| Original language | English |
|---|---|
| Title of host publication | Cognitive Machine Intelligence |
| Subtitle of host publication | Applications, Challenges, and Related Technologies |
| Publisher | CRC Press |
| Pages | 290-308 |
| Number of pages | 19 |
| ISBN (Electronic) | 9781040097083 |
| ISBN (Print) | 9781032647432 |
| DOIs | |
| Publication status | Published - 28 Aug 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 13 Climate Action
ASJC Scopus subject areas
- General Computer Science
- General Engineering
- General Energy
- General Environmental Science
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