A novel genetic-algorithm-based neural network for short-term load forecasting

S. H. Ling; Hung Fat Frank Leung; H. K. Lam; Yim Shu Lee; Peter K S Tam

doi:10.1109/TIE.2003.814869

A novel genetic-algorithm-based neural network for short-term load forecasting

S. H. Ling, Hung Fat Frank Leung, H. K. Lam, Yim Shu Lee, Peter K S Tam

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

117 Citations (Scopus)

Abstract

This paper presents a neural network with a novel neuron model. In this model, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. This neural network provides better performance than a traditional feedforward neural network, and fewer hidden nodes are needed. The parameters of the proposed neural network are tuned by a genetic algorithm with arithmetic crossover and nonuniform mutation. Some applications are given to show the merits of the proposed neural network.

Original language	English
Pages (from-to)	793-799
Number of pages	7
Journal	IEEE Transactions on Industrial Electronics
Volume	50
Issue number	4
DOIs	https://doi.org/10.1109/TIE.2003.814869
Publication status	Published - 1 Aug 2003

Keywords

Genetic algorithm (GA)
Neural network
Short-term load forecasting

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

More information

10.1109/TIE.2003.814869

http://hdl.handle.net/10397/1405

Cite this

@article{634c6803df6540ad852a89ea4ed69b93,

title = "A novel genetic-algorithm-based neural network for short-term load forecasting",

abstract = "This paper presents a neural network with a novel neuron model. In this model, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. This neural network provides better performance than a traditional feedforward neural network, and fewer hidden nodes are needed. The parameters of the proposed neural network are tuned by a genetic algorithm with arithmetic crossover and nonuniform mutation. Some applications are given to show the merits of the proposed neural network.",

keywords = "Genetic algorithm (GA), Neural network, Short-term load forecasting",

author = "Ling, {S. H.} and Leung, {Hung Fat Frank} and Lam, {H. K.} and Lee, {Yim Shu} and Tam, {Peter K S}",

year = "2003",

month = aug,

day = "1",

doi = "10.1109/TIE.2003.814869",

language = "English",

volume = "50",

pages = "793--799",

journal = "IEEE Transactions on Industrial Electronics",

issn = "0278-0046",

publisher = "IEEE Industrial Electronics Society",

number = "4",

}

TY - JOUR

T1 - A novel genetic-algorithm-based neural network for short-term load forecasting

AU - Ling, S. H.

AU - Leung, Hung Fat Frank

AU - Lam, H. K.

AU - Lee, Yim Shu

AU - Tam, Peter K S

PY - 2003/8/1

Y1 - 2003/8/1

N2 - This paper presents a neural network with a novel neuron model. In this model, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. This neural network provides better performance than a traditional feedforward neural network, and fewer hidden nodes are needed. The parameters of the proposed neural network are tuned by a genetic algorithm with arithmetic crossover and nonuniform mutation. Some applications are given to show the merits of the proposed neural network.

AB - This paper presents a neural network with a novel neuron model. In this model, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. This neural network provides better performance than a traditional feedforward neural network, and fewer hidden nodes are needed. The parameters of the proposed neural network are tuned by a genetic algorithm with arithmetic crossover and nonuniform mutation. Some applications are given to show the merits of the proposed neural network.

KW - Genetic algorithm (GA)

KW - Neural network

KW - Short-term load forecasting

UR - http://www.scopus.com/inward/record.url?scp=0042525889&partnerID=8YFLogxK

U2 - 10.1109/TIE.2003.814869

DO - 10.1109/TIE.2003.814869

M3 - Journal article

SN - 0278-0046

VL - 50

SP - 793

EP - 799

JO - IEEE Transactions on Industrial Electronics

JF - IEEE Transactions on Industrial Electronics

IS - 4

ER -

A novel genetic-algorithm-based neural network for short-term load forecasting

Abstract

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this