Energy conservation and preventive maintenance of equipment require the ability to
accurately predict future trends in shop floor power consumption to keep track of equipment …

The forecast of electrical energy demand has played an increasingly relevant role in
sustainable electrical power system. This paper develops a new method for forecasting …

Traditional data-driven energy consumption forecasting models, including machine learning
and deep learning methods, showed outstanding performance in terms of forecasting …

Accurate and efficient demand forecasting is essential to grid stability, supply, and
management in today's electricity markets. Due to the complex pattern of electric power …

The number of investors in Indonesia increases annually. This is due to the growing
popularity of investing, particularly stock investment. There are currently three largest …

The high quality of Information Technology (IT) equipment undoubtedly contributes to the
seamless functioning of various industries in today's digital era. As organizations strive to …

Energy usage is a critical factor in various human activities, ranging from individual to
industrial scales. It plays a vital role in supporting economic growth, social welfare, and …

This paper aims to explore the relationship between deep learning and forecasting within
the context of the Sustainable Development Goals (SDGs). The primary objective is to …

Building energy consumption takes up over 30% of global final energy use and 26% of
global energy-related emissions. In addition, building operations represent nearly 55% of …

In this paper, we present a generalized stochastic three-factor model to forecast changes in
the industrial production of energy materials. This approach is new as, by deriving a …