Hybridization Solution of Electrical Energy Demand Response and Forecasting Program by Using PSO-LSSVM Technique-Reference-Cited by-同舟云学术

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Hybridization Solution of Electrical Energy Demand Response and Forecasting Program by Using PSO-LSSVM Technique

Published:2023-08-02 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE)
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Author:

Ali Amira Noor Farhanie¹,Sulaima Mohamad Fani¹,Tahir Musthafah Mohd.²,Razak Intan Azmira Wan Abdul¹,Kadir Aida Fazliana Abdul¹,Rahman Zulkifli Ab.³

Affiliation:

1. Universiti Teknikal Malaysia Melaka,Faculty of Electrical Engineering,Durian Tunggal,Malaysia

2. Universiti Teknikal Malaysia Melaka,Faculty of Mechanical Engineering,Durian Tunggal,Malaysia

3. YHS Associates Sdn Bhd organization,Kuala Lumpur,Wilayah Persekutuan

Funder

Ministry of Higher Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10249207/10249013/10249532.pdf?arnumber=10249532

Reference22 articles.

1. Particle swarm optimisation in designing parameters of manufacturing processes: A review (2008–2018)

2. Short-term power load forecasting based on support vector machine and particle swarm optimization;qiang;Journal of Algorithms & Computational Technology,2018

3. A constrained multi-swarm particle swarm optimization without velocity for constrained optimization problems

4. Artificial Intelligence Application in Demand Response: Advantages, Issues, Status, and Challenges

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