GSMIS

Publication

Journal Publication

Title of Article

Generalized stability of artificial emotional neural network in predicting domestic power peak demand

Date of Acceptance

18 November 2022

Journal

Title of Journal

Science, Engineering and Health Studies (SEHS)

Standard

SCOPUS

Institute of Journal

Silpakorn University Science and Technology Journal

ISBN/ISSN

2630-0087

Volume

2022

Issue

Month

Year of Publication

2022

Page

Abstract

Predicting an optimal domestic power peak demand is very important for long-term electricity construction planning as the electricity cannot be stored permanently. If the prediction can give a yield close to the actual demand, the electricity suppliers can save their construction costs and provide their customers with a lower cost of electricity. However, accurate predictions still require improvement. This work, therefore, presented the predicting problem using a modified artificial emotional neural network (AENN) based on an improved JAYA optimizer. This study also applied extreme learning machine (ELM) to compute the expanded feature in the AENN. A real case study of Thailand’s power peak demand was considered, which was prepared using a rolling mechanism, to demonstrate the performance of a developed predicting model when contrasted with state-of-the-art of AENN models, artificial neural network with Levenberg-Marquardt, AENN methods based on winner-take-all approach, and improved brain emotional learning-based AENNmodel. Performance analyses demonstrated that the proposed model provided improvements in performance and generalized stability over the comparative models.

Keyword

Domestic power peak demand; artificial emotional neural network; improved JAYA optimization algorithm; extreme learning machine

Author

587020034-3	Miss SUTHASINEE IAMSA-AT [Main Author]
	College of Computing Doctoral Degree

Reviewing Status

มีผู้ประเมินอิสระ

Status

ตีพิมพ์แล้ว

Level of Publication

นานาชาติ

citation

true

Part of thesis

true

Attach file

Citation