With the advancement of Machine Learning, since its beginning and over the last years, a
special attention has been given to the Artificial Neural Network. As an inspiration from …

The rapid increase in urbanization has resulted in a significant rise in electricity
consumption, which resulted in a wide gap between the amount of electricity generated and …

Society's concerns with electricity consumption have motivated researchers to improve on
the way that energy consumption management is done. The reduction of energy …

Anomaly detection in specific datasets involves the detection of circumstances that are
common in a homogeneous data. When looking at network traffic data, it is generally difficult …

Artificial Neural networks (ANN) are powerful and effective tools in time-series applications.
The first aim of this paper is to diagnose better and more efficient ANN models (Back …

This work comes as part of the recent continuous and increasing interest in Wavelet
Transforms (WT) and Artificial Neural Networks (ANN). This paper introduces a novel hybrid …

Learning on time series, especially on the small seasonal time series, has a wide range of
practical applications. In this paper, to improve the learning effect on small seasonal time …

This research aims to study and analyze which type of Artificial Neural Network (ANN) is
more efficient and suitable in handling nonhomogenous variance for financial series. Apart …

Our task is to forecast the next day's power consumption in the half-hour interval for a total of
48 intervals. There are many studies that proposed models for power consumption …

The research objective is to discuss the adoption of the wavelet transformation method (WT)
in processing time series, for its efficiency. As well as comparing modern methods …