The potato is a key crop in addressing global hunger, and deep learning is at the core of
smart agriculture. Applying deep learning (eg, YOLO series, ResNet, CNN, LSTM, etc.) in …

With major ramifications for agriculture, water resource management, and disaster planning,
rainfall prediction is an essential component of weather forecasting. The use of big data …

Agriculture is the very important sector of each country, where the gross domestic pay relies
on it. The outcome of the agriculture or crop management was completely based on the end …

Using artificial intelligence to anticipate weather conditions, according to prior research, can
provide positive results. Forecasts of meteorological time series can aid disaster-prevention …

Network security has benefited from intrusion detection, which may spot unexpected threats
from network traffic. Modern methods for detecting network anomalies typically rely on …

The current study used seven optimization algorithms such as stochastic gradient descent
(SGD), root mean square propagation (RMSprop), adaptive grad (AdaGrad), adaptive delta …

As excessive rain may cause numerous disasters, rainfall prediction is very crucial and the
prediction should be realistic since it encourages individuals to take preventative steps. This …

Plants' need for water has become a topic of research for the agriculture industry. The fact
that plant species are very diverse and each plant's need for water varies makes it difficult to …

Recently, the amount of electricity produced worldwide from renewable energy sources has
increased significantly, with the United States leading the way. Wind speed forecasting has …

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 …