Balancing the production and consumption of electricity is an urgent task. Its implementation
largely depends on the means and methods of planning electricity production. Forecasting is …

Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …

Due to rapid development in information technology in both hardware and software, deep
neural networks for regression have become widely used in many fields. The optimization of …

Reliable electricity price forecasts are of great importance to operators and participants in
power markets. However, due to mixing effects of various factors, electricity price fluctuations …

Nowadays, electric load forecasting through a data analytic approach has become one of
the most active and emerging research areas. It provides future consumption patterns of …

A smart grid is a new type of power system based on modern information technology, which
utilises advanced communication, computing and control technologies and employs …

Colon cancer is one of the world's three most deadly and severe cancers. As with any
cancer, the key priority is early detection. Deep learning (DL) applications have recently …

In the smart grid (SG), user consumption data are increasing very rapidly. Some users
consume electricity legally, while others steal it. Electricity theft causes significant damage to …

Traditional electricity price forecasting tends to adopt time-domain forecasting methods
based on time series, which fail to make full use of the regional information of the electricity …

Current technological advances are paving the way for technologies based on deep
learning to be utilized in the majority of life fields. The effectiveness of these technologies …