Deep learning based short-range forecasting of Indian summer monsoon rainfall using earth observation and ground station datasets
We develop a deep learning model (DL) for Indian Summer Monsoon (ISM) short-range
precipitation forecasting using a ConvLSTM network. The model is built using daily …
precipitation forecasting using a ConvLSTM network. The model is built using daily …
PM2. 5 forecasting model using a combination of deep learning and statistical feature selection
This paper proposed a PM 2.5 forecasting model using Long Short-Term Model (LSTM)
sequence to sequence combined with the statistical method. Correlation Analysis, XGBoost …
sequence to sequence combined with the statistical method. Correlation Analysis, XGBoost …
A survey of rainfall prediction using deep learning
Prediction of rainfall is a difficult task because of the high volatility and complicated nature of
the atmospheric data. Recently, various deep learning methods were successfully applied to …
the atmospheric data. Recently, various deep learning methods were successfully applied to …
Machine learning for Earth System Science (ESS): A survey, status and future directions for South Asia
This survey focuses on the current problems in Earth systems science where machine
learning algorithms can be applied. It provides an overview of previous work, ongoing work …
learning algorithms can be applied. It provides an overview of previous work, ongoing work …
Artificial intelligence and machine learning in earth system sciences with special reference to climate science and meteorology in South Asia.
This study focuses on the current problems in earth system science (ESS), where machine
learning (ML) algorithms can be applied. It provides an overview of previous studies …
learning (ML) algorithms can be applied. It provides an overview of previous studies …
Application of different artificial neural network for streamflow forecasting
Time series of future streamflow plays a vital role in planning, designing, and management
of the water resources system. There are many forecasting methods available and most of …
of the water resources system. There are many forecasting methods available and most of …
Analysis and Forecasting of Temporal Rainfall Variability Over Hundred Indian Cities Using Deep Learning Approaches
India, a topographically and meteorologically rich country, has a vast range of rainfall
variability. The impacts could be realized across various sectors, including agriculture …
variability. The impacts could be realized across various sectors, including agriculture …
PM2. 5 forecasting using LSTM sequence to sequence model in Taichung City
Accuracy and speed are crucial in the machine learning forecasting. Specifically, when
encountering high variance segments like sequence forecasting case. For example, air …
encountering high variance segments like sequence forecasting case. For example, air …
Hybrid Particle Swarm Optimized Models for Rainfall Prediction: A Case Study in India
Predicting rainfall is crucial across multiple sectors and activities, impacting agriculture,
water management and disaster preparedness. In this study, the Particle Swarm …
water management and disaster preparedness. In this study, the Particle Swarm …
A Comparative Study of Long Short-Term Memory for Rainfall Prediction in India
Researchers extensively studied the prediction of rainfall due to its significant impact on the
environment and the daily lives of individuals. In this study, four LSTM models were applied …
environment and the daily lives of individuals. In this study, four LSTM models were applied …