Artificial neural network for forecasting residential electrical energy

Abdallah Al-Shehri

doi:10.1002/(sici)1099-114x(19990625)23:8<649::aid-er490>3.0.co;2-t

Artificial neural network for forecasting residential electrical energy

Abdallah Al-Shehri^*

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

An artificial neural network (ANN) model for forecasting the residential electrical energy (REE) in the Eastern Province of Saudi Arabia is presented. A comparison of the neural model with the polynomial fit is made for validation purposes. The results show that the forecasting of the REE predicted by the ANN is closer to the real data than that predicted by the polynomial fit model.

Original language	English
Pages (from-to)	649-661
Number of pages	13
Journal	International Journal of Energy Research
Volume	23
Issue number	8
DOIs	https://doi.org/10.1002/(sici)1099-114x(19990625)23:8<649::aid-er490>3.0.co;2-t
State	Published - 25 Jun 1999

Keywords

Electrical energy
Forecasting
Modelling
Neural network
Polynomial fit

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
Nuclear Energy and Engineering
Fuel Technology
Energy Engineering and Power Technology

Access to Document

10.1002/(sici)1099-114x(19990625)23:8<649::aid-er490>3.0.co;2-t

Cite this

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title = "Artificial neural network for forecasting residential electrical energy",

abstract = "An artificial neural network (ANN) model for forecasting the residential electrical energy (REE) in the Eastern Province of Saudi Arabia is presented. A comparison of the neural model with the polynomial fit is made for validation purposes. The results show that the forecasting of the REE predicted by the ANN is closer to the real data than that predicted by the polynomial fit model.",

keywords = "Electrical energy, Forecasting, Modelling, Neural network, Polynomial fit",

author = "Abdallah Al-Shehri",

year = "1999",

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T1 - Artificial neural network for forecasting residential electrical energy

AU - Al-Shehri, Abdallah

PY - 1999/6/25

Y1 - 1999/6/25

N2 - An artificial neural network (ANN) model for forecasting the residential electrical energy (REE) in the Eastern Province of Saudi Arabia is presented. A comparison of the neural model with the polynomial fit is made for validation purposes. The results show that the forecasting of the REE predicted by the ANN is closer to the real data than that predicted by the polynomial fit model.

AB - An artificial neural network (ANN) model for forecasting the residential electrical energy (REE) in the Eastern Province of Saudi Arabia is presented. A comparison of the neural model with the polynomial fit is made for validation purposes. The results show that the forecasting of the REE predicted by the ANN is closer to the real data than that predicted by the polynomial fit model.

KW - Electrical energy

KW - Forecasting

KW - Modelling

KW - Neural network

KW - Polynomial fit

UR - https://www.scopus.com/pages/publications/0041191191

U2 - 10.1002/(sici)1099-114x(19990625)23:8<649::aid-er490>3.0.co;2-t

DO - 10.1002/(sici)1099-114x(19990625)23:8<649::aid-er490>3.0.co;2-t

M3 - Article

AN - SCOPUS:0041191191

SN - 0363-907X

VL - 23

SP - 649

EP - 661

JO - International Journal of Energy Research

JF - International Journal of Energy Research

IS - 8

ER -

Artificial neural network for forecasting residential electrical energy

Abstract

Keywords

ASJC Scopus subject areas

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