A load curve based fuzzy modeling technique for short-term load forecasting
type: Item
instance of: scholarly article
title: A load curve based fuzzy modeling technique for short-term load forecasting
zbMATH Open document ID: 1031.93011
DOI: 10.1016/S0165-0114(02)00211-7
author: S. E. Papadakis
author: A. Bakirtzis
author: J. B. Theocharis
published in: Fuzzy Sets and Systems
publication date: 2003-05-22T00:00:00Z
review text: The authors propose a fuzzy rule-based model for short-term forecasting. Its development is carried out in a general setting of Computational Intelligence and comprises three main phases; that is (a) determination of the structure of the model, (b) selecting input variables through genetic optimization (genetic algorithm), and (c) fine tuning of the model through a hybrid of the genetic/least square error algorithm. The effectiveness of the model is augmented by the realization of the conclusion part in the form of cubic B-splines. The study comes with an extensive experimental part including some comparative analysis exploiting other neural network models.
reviewed by: Witold Pedrycz
Mathematics Subject Classification ID: 93A30
Mathematics Subject Classification ID: 93C42
zbMATH DE Number: 1915152
zbMATH Keywords: Fuzzy modeling
zbMATH Keywords: Fuzzy clustering
zbMATH Keywords: Fuzzy C-regression method
zbMATH Keywords: Cubic B-splines
zbMATH Keywords: Genetic algorithms
zbMATH Keywords: Short-term load forecasting
MaRDI profile type: Publication
cites work: Q3969900
cites work: Q3799870
cites work: Constrained minimum-time path planning for robot manipulators via virtual knots of the cubic B-spline functions
full work available at URL: s0165-0114(02)00211-7
OpenAlex ID: W2022150664
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description: scientific article; zbMATH DE number 1915152