Electricity is conceivably the most multipurpose energy carrier in modern global economy,
and therefore primarily linked to human and economic development. Energy sector reform is …

Agricultural price prediction is a hot research topic in the field of agriculture, and accurate
prediction of agricultural prices is crucial to realize the sustainable and healthy development …

Wavelet transform (WT), as a data preprocessing algorithm, has been widely applied in
electricity price forecasting. However, this deterministic-based algorithm does not present …

Traditionally, short-term electricity price forecasting has been essential for utilities and
generation companies. However, the deregulation of electricity markets created a …

Recently, grey system, neural network, and fractional order calculus theory have become
popular research areas, and an increasing number of scholars have joined these studies …

Accurate electricity price forecasting is a formidable challenge for market participants and
managers owing to high volatility of the electricity prices. Price forecasting is also the most …

The purpose of this paper is to model electricity consumption using Artificial Neural
Networks (ANN). Total electricity consumption and consumption generated by households …

A novel methodology based on neural networks is presented to forecast day-ahead
electricity spikes and prices. Day-ahead electricity prices are forecasted by the first neural …

In this paper we investigate the efficiency of a support vector machine (SVM)-based
forecasting model for the next-day directional change of electricity prices. We first adjust the …

Traders and practitioners in diverse power exchanges are nowadays being most exposed to
uncertainty than ever. The combination of several factors such as renewable generation and …