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Publication
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| 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 |
16 |
| Month |
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| Year of Publication |
2022 |
| Page |
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| 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 |
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| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ตีพิมพ์แล้ว |
| Level of Publication |
นานาชาติ |
| citation |
true |
| Part of thesis |
true |
| Attach file |
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| Citation |
0
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Journal Publication
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