A Survey of Weather Forecasting based on Machine Learning and Deep Learning Techniques
Mihir Bhawsar, Vandan Tewari, Preeti Khare, D Sanjay, Sawaitul, Prof, Dr Wagh, Chatur, Fahad Sheikh, S Karthick, D Malathi, J Sudarsan, C Arun, Wenying Zhang, Huaguang Zhang, Fellow, Jinhai Ieee, Kai Liu, Dongsheng Li, Hui Yang, Tian, G Vamsi, Krishna, Priyanka Janani, Sebastian, R Samya, R Rathipriya, Divya Chauhan, Jawahar Thakur, Prashant Biradar, Sarfraz Ansari, Savita Yashavantparadkar, Lohiya, Arpit Tiwari, S Verma, Wakode Badhiyes, P Chatur, Rupa, P Kalaiyarasi, Mrs Kalaiselvi, C Kunjumon, S Nair, D Rajan, S, P Suresh, S Preetha, L Han, J Sun, W Zhang, P Zhang, Y Jia, J Gao, W Song, H Leung, K Yonekura, H Hattori, T Suzuki, V Nikam, B Meshram, A Salman, B Kanigoro, Y Heryadi, Bhanu Kolla, Naga Pawan, Y V R & Kalyani, Lakshmi &vadla, Pradeep
Abstract
Forecast of future weather is one of the dominant concerns in today’s era. Several techniques that have been used to forecast future weather are statistical analysis, machine learning, and deep learning techniques. Forecast of weather can assist in the decision-making process for the prevention of disasters. While forecasting weekly weather can help people, decide and manage their activities and recreational programs it can also help Smart management programs. The accuracy of the Short term ambient forecast conditions is particularly conducive to the development of forecast management strategies. This paper presents an inclusive survey on such methods based on Machine Learning, and Deep Learning Techniques used to predict weather and discusses the applications, types, and problems of the forecasting.