Ensemble of genetic programming models for designing reactive power controllers
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{grosan:2005:HIS,
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author = "C. Grosan and A. Abraham",
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title = "Ensemble of genetic programming models for designing
reactive power controllers",
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booktitle = "Fifth International Conference on Hybrid Intelligent
Systems, HIS-05",
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year = "2005",
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month = "6-9 " # nov,
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICHIS.2005.36",
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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
Citations