Short-Term Electric Power Demand Forecasting Using NSGA II-ANFIS Model

Short-Term Electric Power Demand Forecasting Using NSGA II-ANFIS Model

Load forecasting is of crucial importance for smart grids and the electricity market in terms of the meeting the demand for and distribution of electrical energy. This research proposes a hybrid algorithm for improving the forecasting accuracy where a non-dominated sorting genetic algorithm II (NSGA...

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Bibliographic Details
Main Authors: Aydin Jadidi, Raimundo Menezes, Nilmar de Souza, Antonio Cezar de Castro Lima
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Energies
Subjects:
electric load forecasting
non-dominated sorting genetic algorithm II
multi-layer perceptron
adaptive neuro-fuzzy inference system
meta-heuristic algorithms
Online Access:https://www.mdpi.com/1996-1073/12/10/1891

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https://www.mdpi.com/1996-1073/12/10/1891

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