Smart industries use modern technologies such as machine learning and big data to
maintain supply chain management and increase productivity but still the main challenge …

This study proposes a new convolutional neural network (CNN) method with an input-signal
decomposition algorithm. With the proposed CNN architecture, hourly electricity …

With the development of global intelligence industry and new energy systems, the role of
load forecasting is increasingly prominent. This article reviews the research progress and …

Background: Load forecasting is a crucial element in power utility business load forecasting
and has influenced key decision-makers in the industry to predict future energy demand with …

Grain storage has very strict temperature requirements. Aiming at the problems of nonlinear
characteristics and poor prediction accuracy of temperature parameters in grain storage, a …

Background: Automatic recognition of cough sounds shows promise in the diagnosis of
respiratory conditions. This study investigated the diagnostic value of cough sounds in …

The coronavirus (COVID-19) outbreak has presented unprecedented challenges to utilities
and grid administrators worldwide. One area of particular concern is load forecasting, as the …

Sinüzoidal sinyal yapısında akım taşınan enterkonnekte sistemin kararlı olarak çalışabilmesi
için şebeke frekansının kabul edilebilir limitler içinde kalması gerekmektedir. Şebeke …

In this paper, the GA-SVR model is constructed to predict maritime traffic accidents, in which
the penalty parameter C, the kernel function parameter σ and the insensitive loss function ε …