Short-term load forecasting of power systems by gene expression programming
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- @Article{journals/nca/HosseiniG12,
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author = "Seyyed Soheil {Sadat Hosseini} and
Amir Hossein Gandomi",
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title = "Short-term load forecasting of power systems by gene
expression programming",
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journal = "Neural Computing and Applications",
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year = "2012",
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number = "2",
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volume = "21",
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pages = "377--389",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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ISSN = "0941-0643",
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DOI = "doi:10.1007/s00521-010-0444-y",
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size = "Special Issue on Theory and applications of swarm
intelligence",
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abstract = "Short-term load forecasting is a popular topic in the
electric power industry due to its essentiality in
energy system planning and operation. Load forecasting
is important in deregulated power systems since an
improvement of a few percentages in the prediction
accuracy will bring benefits worth of millions of
dollars. In this study, a promising variant of genetic
programming, namely gene expression programming (GEP),
is used to improve the accuracy and enhance the
robustness of load forecasting results. With the use of
the GEP technique, accurate relationships were obtained
to correlate the peak and total loads to average,
maximum and lowest temperatures of day. The presented
model is applied to forecast short-term load using the
actual data from a North American electric utility. A
multiple least squares regression analysis was
performed using the same variables and same data sets
to benchmark the GEP models. For more verification, a
subsequent parametric study was also carried out. The
observed agreement between the predicted and measured
peak and total load values indicates that the proposed
correlations are capable of effectively forecasting the
short-term load. The GEP-based formulae are relatively
short, simple and particularly valuable for providing
an analysis tool accessible to practising engineers.",
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affiliation = "Tafresh University, Tafresh, Iran",
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bibdate = "2012-02-24",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/nca/nca21.html#HosseiniG12",
- }
Genetic Programming entries for
S S Sadat Hosseini
A H Gandomi
Citations