Horticultural products such as fruits, vegetables, and tea offer a range of important nutrients
such as protein, carbohydrates, vitamins and lipids. However, the present yield and quality …

Abstract Peer-to-Peer (P2P) energy trading has gained much attention recently due to the
advanced development of distributed energy resources. P2P enables prosumers to trade …

Accurate prediction of monthly runoff is critical for effective water resource management and
flood forecasting in river basins. In this study, we developed a hybrid deep learning (DL) …

This paper proposes new improved binary versions of the Sine Cosine Algorithm (SCA) for
the Feature Selection (FS) problem. FS is an essential machine learning and data mining …

Temperature forecasting is a crucial aspect of meteorology and climate change studies, but
challenges arise due to the complexity of time series data involving seasonal patterns and …

Short-term load forecasting (STLF) is critical for ensuring smooth and efficient functioning of
power systems. In this study, a prediction approach, combining ensemble empirical mode …

This study presents a recurrent neural network (RNN)-based model for predicting physical
quality changes in onions during long-term low-temperature storage. Unlike previous …

Effective workforce forecasting is critical to strategic management in construction projects,
particularly ensuring staffing is optimized for efficient and timely project completion. This …

The study of multivariate time series forecasting (MTSF) problems has high significance in
many areas, such as industrial forecasting and traffic flow forecasting. Traditional forecasting …

The frequent and sharp fluctuations in garlic prices seriously affect the sustainable
development of the garlic industry. Accurate prediction of garlic prices can facilitate correct …