Abstract Machine learning algorithms have been extensively exploited in energy research,
due to their flexibility, automation and ability to handle big data. Among the most prominent …

Stock forecasting is a complicated and daily challenge for investors because of the non-
linearity of the market and the high volatility of financial assets such as stocks, bonds and …

With the intensification of anthropogenic warming and urbanization, high‐temperature
weather poses an enormous threat to socio‐economic and human healthy. However, the …

Permanent grasslands play a very important role in the landscape. The loss of permanent
grasslands and their subsequent conversion into arable land create erosion-prone …

Sulfur dioxide (SO 2) is primarily released through industrial, residential, and transportation
activities, and creates secondary air pollutants through chemical reactions in the …

Buildings account for approximately 40% of the total global energy consumption. Therefore,
accurate prediction of building energy consumption is necessary to optimize resource …

The field of machine learning (ML) and explainable artificial intelligence (XAI) has
developed rapidly the last ten years. This development has generated increased interest in …

This reviewed literature on electricity forecasting covers its history, terminology, and
techniques. A systematic review of existing studies highlighted key findings and future …

Artificial intelligence and machine learning have become one of the fastest growing and
most popular fields in technology today. Classification algorithms constitute one of the …

Earnings per share is considered one of the most relevant factors in determining the price of
shares and the value of companies. So, apart from the fact that most individual investors …