Genetic-based multi-layered perceptrons for Taiwan power system short term load forecasting

Shyh Jier Huang; Ching Lien Huang

Genetic-based multi-layered perceptrons for Taiwan power system short term load forecasting

Department of Electrical Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

A new approach of using genetic algorithms based multi-layered perceptrons (GA-MLP) to solve short term load forecasting problems is proposed in this paper. Merits of genetic algorithms are included to prevent the learning stagnation in the neural network learning process. The proposed method is tested on the load data from Taiwan Power Company. The results demonstrate the feasibility of the proposed approach to applications.

Original language	English
Pages	785-790
Number of pages	6
Publication status	Published - 1995 Dec 1
Event	Proceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95 - St.Louis, MO, USA Duration: 1995 Nov 12 → 1995 Nov 15

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Other	Proceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95
City	St.Louis, MO, USA
Period	95-11-12 → 95-11-15

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title = "Genetic-based multi-layered perceptrons for Taiwan power system short term load forecasting",

abstract = "A new approach of using genetic algorithms based multi-layered perceptrons (GA-MLP) to solve short term load forecasting problems is proposed in this paper. Merits of genetic algorithms are included to prevent the learning stagnation in the neural network learning process. The proposed method is tested on the load data from Taiwan Power Company. The results demonstrate the feasibility of the proposed approach to applications.",

author = "Huang, {Shyh Jier} and Huang, {Ching Lien}",

year = "1995",

month = dec,

day = "1",

language = "English",

pages = "785--790",

note = "Proceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95 ; Conference date: 12-11-1995 Through 15-11-1995",

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AU - Huang, Shyh Jier

AU - Huang, Ching Lien

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N2 - A new approach of using genetic algorithms based multi-layered perceptrons (GA-MLP) to solve short term load forecasting problems is proposed in this paper. Merits of genetic algorithms are included to prevent the learning stagnation in the neural network learning process. The proposed method is tested on the load data from Taiwan Power Company. The results demonstrate the feasibility of the proposed approach to applications.

AB - A new approach of using genetic algorithms based multi-layered perceptrons (GA-MLP) to solve short term load forecasting problems is proposed in this paper. Merits of genetic algorithms are included to prevent the learning stagnation in the neural network learning process. The proposed method is tested on the load data from Taiwan Power Company. The results demonstrate the feasibility of the proposed approach to applications.

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M3 - Paper

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T2 - Proceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95

Y2 - 12 November 1995 through 15 November 1995

ER -

Genetic-based multi-layered perceptrons for Taiwan power system short term load forecasting

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