Forecasting energy time-series data using a fuzzy ARTMAP neural network

Abstract

Time-series forecasting is an important field of machine learning and is fundamental in analyzing trends based on historical data from various sources. In this paper, a fuzzy ARTMAP neural network for time-series forecasting is presented. To validate the proposed system, two energy-related datasets from Great Britain were selected. With a promising processing time and accuracy as good as a traditional machine learning algorithm, the fuzzy ARTMAP neural network has shown that can be a good option to perform forecasting considering different time-based data issues.