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- Vol. 5 Issue 4
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Advanced Weather Prediction Using AI
Authors
1234B. tech, Department of Information Technology, CMR Engineering College, Hyderabad, Telangana, India. 5Professor, Department of Information Technology, CMR Engineering College, Hyderabad, Telangana, India.
Article Information
- Published In
- Volume 5, Issue 4 (2025)
- Published Online
- July-August 2025
- Pages
- 21-27
- Article Type
- Original Article
- Check for updates
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References
[1] Ravi, V., & Suresh, K., "Deep learning-based meteorological predictions using CNN and LSTM models[J]", International Journal of Computer Applications, vol. 182, no. 48, pp. 20–25, 2024.
[2] Singh, R., & Verma, A., "Machine Learning Techniques for Short-Term Weather Forecasting[J]", Journal of Atmospheric and Climate Studies, vol. 9, no. 3, pp. 45–51, 2023.
[3] Zhang, Y., & Wu, H., "Hybrid Neural Network Models for Climate Data Analysis[J]", IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1112–1120, 2024.
[4] Kumar, N., & Mehta, S., "AI and Remote Sensing Data for Severe Weather Detection[J]", International Journal of Environmental Science and Technology, vol. 21, no. 1, pp. 78–84, 2023.
[5] Li, J., & Chen, F., "Real-Time Weather Forecasting with IoT Sensor Networks and AI Algorithms[J]", Sensors and Actuators A: Physical, vol. 347, 113927, 2024.
[6] Roy, P., & Das, B., "CNN-LSTM Based Rainfall Prediction Using Satellite Imagery[J]", Advances in Intelligent Systems and Computing, vol. 1512, pp. 312– 320, 2023.
[7] Guo RongBin and Zhao XiuCai, "The trend of automatic test system," Foreign Electronic Measurement Technology, vol. 33, no. 6, 2024.
[8] Yang Aibing, Sun Ye and Peng Wei, "Research on the software development model of automatic test system," INDUSTRIAL INSTRUMENTATION & AUTOMATION, vol. 6, pp. 16-18, 2023.
[9] Rasp S., Dueben P. D., Scher S., Weyn J. A., Mouatadid S., and Thuerey N., "WeatherBench: A benchmark dataset for data-driven weather forecasting," Quarterly Journal of the Royal Meteorological Society, vol. 146, no. 730, pp. 1741–1758, 2020.
[10] Lagerquist R., McGovern A., and Smith T., "Deep learning for real-time forecasts of damaging straight-line convective winds," Weather and Forecasting, vol. 35, no. 3, pp. 1117–1140, 2020.
[11] Weyn J. A., Durran D. R., and Caruana R., "Improving data-driven global weather prediction using deep convolutional neural networks," Journal of Advances in Modeling Earth Systems, vol. 12, no. 9, 2020.
[12] Shi X., Chen Z., Wang H., Yeung D. Y., Wong W., and Woo W., "Convolutional LSTM network: A machine learning approach for precipitation nowcasting," in Advances in Neural Information Processing Systems (NeurIPS), pp. 802–810, 2015.
[13] Ravuri S., et al., "Skillful precipitation nowcasting using deep generative models of radar," Nature, vol. 597, no. 7878, pp. 672–677, 2021.
[14] Scher S., "Toward data-driven weather and climate forecasting: Approximating a simple general circulation model with deep learning," Geophysical Research Letters, vol. 45, no. 22, pp. 12,616–12,622, 2018.
[15] Ham Y. G., Kim J. H., and Luo J. J., "Deep learning for multi-year ENSO forecasts," Nature, vol. 573, no. 7775, pp. 568–572, 2019.
[2] Singh, R., & Verma, A., "Machine Learning Techniques for Short-Term Weather Forecasting[J]", Journal of Atmospheric and Climate Studies, vol. 9, no. 3, pp. 45–51, 2023.
[3] Zhang, Y., & Wu, H., "Hybrid Neural Network Models for Climate Data Analysis[J]", IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1112–1120, 2024.
[4] Kumar, N., & Mehta, S., "AI and Remote Sensing Data for Severe Weather Detection[J]", International Journal of Environmental Science and Technology, vol. 21, no. 1, pp. 78–84, 2023.
[5] Li, J., & Chen, F., "Real-Time Weather Forecasting with IoT Sensor Networks and AI Algorithms[J]", Sensors and Actuators A: Physical, vol. 347, 113927, 2024.
[6] Roy, P., & Das, B., "CNN-LSTM Based Rainfall Prediction Using Satellite Imagery[J]", Advances in Intelligent Systems and Computing, vol. 1512, pp. 312– 320, 2023.
[7] Guo RongBin and Zhao XiuCai, "The trend of automatic test system," Foreign Electronic Measurement Technology, vol. 33, no. 6, 2024.
[8] Yang Aibing, Sun Ye and Peng Wei, "Research on the software development model of automatic test system," INDUSTRIAL INSTRUMENTATION & AUTOMATION, vol. 6, pp. 16-18, 2023.
[9] Rasp S., Dueben P. D., Scher S., Weyn J. A., Mouatadid S., and Thuerey N., "WeatherBench: A benchmark dataset for data-driven weather forecasting," Quarterly Journal of the Royal Meteorological Society, vol. 146, no. 730, pp. 1741–1758, 2020.
[10] Lagerquist R., McGovern A., and Smith T., "Deep learning for real-time forecasts of damaging straight-line convective winds," Weather and Forecasting, vol. 35, no. 3, pp. 1117–1140, 2020.
[11] Weyn J. A., Durran D. R., and Caruana R., "Improving data-driven global weather prediction using deep convolutional neural networks," Journal of Advances in Modeling Earth Systems, vol. 12, no. 9, 2020.
[12] Shi X., Chen Z., Wang H., Yeung D. Y., Wong W., and Woo W., "Convolutional LSTM network: A machine learning approach for precipitation nowcasting," in Advances in Neural Information Processing Systems (NeurIPS), pp. 802–810, 2015.
[13] Ravuri S., et al., "Skillful precipitation nowcasting using deep generative models of radar," Nature, vol. 597, no. 7878, pp. 672–677, 2021.
[14] Scher S., "Toward data-driven weather and climate forecasting: Approximating a simple general circulation model with deep learning," Geophysical Research Letters, vol. 45, no. 22, pp. 12,616–12,622, 2018.
[15] Ham Y. G., Kim J. H., and Luo J. J., "Deep learning for multi-year ENSO forecasts," Nature, vol. 573, no. 7775, pp. 568–572, 2019.
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