Hybrid Particle Swarm Optimization With Genetic Algorithm to Train Artificial Neural Networks for Short-Term Load Forecasting

Kuruge Darshana Abeyrathna and Chawalit Jeenanunta
Additional contact information
Kuruge Darshana Abeyrathna: Centre for Artificial Intelligence Research, University of Agder, Grimstad, Norway
Chawalit Jeenanunta: Sirindhorn International Institute of Technology, Thammasat University, Pathumthani, Thailand

International Journal of Swarm Intelligence Research (IJSIR), 2019, vol. 10, issue 1, 1-14

Abstract: This research proposes a new training algorithm for artificial neural networks (ANNs) to improve the short-term load forecasting (STLF) performance. The proposed algorithm overcomes the so-called training issue in ANNs, where it traps in local minima, by applying genetic algorithm operations in particle swarm optimization when it converges to local minima. The training ability of the hybridized training algorithm is evaluated using load data gathered by Electricity Generating Authority of Thailand. The ANN is trained using the new training algorithm with one-year data to forecast equal 48 periods of each day in 2013. During the testing phase, a mean absolute percentage error (MAPE) is used to evaluate performance of the hybridized training algorithm and compare them with MAPEs from Backpropagation, GA, and PSO. Yearly average MAPE and the average MAPEs for weekdays, Mondays, weekends, Holidays, and Bridging holidays show that PSO+GA algorithm outperforms other training algorithms for STLF.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJSIR.2019010101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:10:y:2019:i:1:p:1-14

Access Statistics for this article

International Journal of Swarm Intelligence Research (IJSIR) is currently edited by Yuhui Shi

More articles in International Journal of Swarm Intelligence Research (IJSIR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().