In alignment with the rapid development of artificial intelligence in the era of data
management, the application domains for machine learning have expanded to all …

The ongoing transition in the electricity market, coupled with the rising penetration of
renewable energy sources, has spurred demand for enhanced load forecasting accuracy …

Contemporary wind speed prediction research methodologies often employ two-stage
decomposition preprocessing techniques to leverage the temporal correlation of wind …

Wind energy is taken as one of the most potential green energy sources, whose accurate
and stable prediction is important to improve the efficiency of wind turbines as well as to …

Abstract 1 Short-term wind speed prediction is critical for enhancing the efficiency of wind
power systems and assuring the stability and continuity of power generation and the host …

Industrial urea synthesis is performed under harsh conditions requiring huge energy
consumption and accompanied by heavy environmental pollution. Electrocatalytic C–N …

Effective managing sustainable supply chain is on the most cutting-edge position of various
organizations in the process of delivering products. There are many optimization …

Climate Change heavily impacts global cities, the downsides of which can be minimized by
adopting renewables like wind energy. However, despite its advantages, the nonlinear …

Accurate prediction of wind speed is significant importance in various applications such as
renewable energy management, weather prediction, and aviation safety. However, more …

Carving out the stochastic wind speed is still a challenge due to its intrinsic nature. With the
wide spread of Internet of Things technology, the amount of data have presented explosive …