Ensemble of genetic programming models for designing reactive power controllers

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{grosan:2005:HIS,

• author = "C. Grosan and A. Abraham",
• title = "Ensemble of genetic programming models for designing reactive power controllers",
• booktitle = "Fifth International Conference on Hybrid Intelligent Systems, HIS-05",
• year = "2005",
• month = "6-9 " # nov,
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICHIS.2005.36",
• abstract = "In this paper, we present an ensemble combination of two genetic programming models namely linear genetic programming (LGP) and multi expression programming (MEP). The proposed model is designed to assist the conventional power control systems with added intelligence. For on-line control, voltage and current are fed into the network after preprocessing and standardisation. The model was trained with a 24-hour load demand pattern and performance of the proposed method is evaluated by comparing the test results with the actual expected values. For performance comparison purposes, we also used an artificial neural network trained by a backpropagation algorithm. Test results reveal that the proposed ensemble method performed better than the individual GP approaches and artificial neural network in terms of accuracy and computational requirements.",

}

Genetic Programming entries for Crina Grosan Ajith Abraham

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