An ensemble model for day-ahead electricity demand time series forecasting

Published: May 21, 2013
Abstract
In this work, we try to solve the problem of day-ahead prediction of electricity demand using an ensemble forecasting model. Based on the Pattern Sequence Similarity (PSF) algorithm, we implemented five forecasting models using different clustering techniques: K-means model (as in original PSF), Self-Organizing Map model, Hierarchical Clustering model, K-medoids model, and Fuzzy C-means model. By incorporating these five models, we then proposed...
Paper Details
Title
An ensemble model for day-ahead electricity demand time series forecasting
Published Date
May 21, 2013
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