Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Lee:2012:Energies,
  author =       "Yi-Shian Lee and Lee-Ing Tong",
  title =        "Predicting High or Low Transfer Efficiency of
                 Photovoltaic Systems Using a Novel Hybrid Methodology
                 Combining Rough Set Theory, Data Envelopment Analysis
                 and Genetic Programming",
  journal =      "Energies",
  year =         "2012",
  volume =       "5",
  number =       "3",
  pages =        "545--560",
  publisher =    "Molecular Diversity Preservation International",
  keywords =     "genetic algorithms, genetic programming, photovoltaic
                 systems, rough set theory, data envelopment analysis,
                 hybrid model",
  ISSN =         "1996-1073; 19961073",
  URL =          "http://www.mdpi.com/1996-1073/5/3/545/pdf",
  URL =          "http://www.mdpi.com/1996-1073/5/3/545/",
  broken =       "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=19961073\&date=2012\&volume=5\&issue=3\&spage=545",
  DOI =          "doi:10.3390/en5030545",
  size =         "16 pages",
  abstract =     "Solar energy has become an important energy source in
                 recent years as it generates less pollution than other
                 energies. A photovoltaic (PV) system, which typically
                 has many components, converts solar energy into
                 electrical energy. With the development of advanced
                 engineering technologies, the transfer efficiency of a
                 PV system has been increased from low to high. The
                 combination of components in a PV system influences its
                 transfer efficiency. Therefore, when predicting the
                 transfer efficiency of a PV system, one must consider
                 the relationship among system components. This work
                 accurately predicts whether transfer efficiency of a PV
                 system is high or low using a novel hybrid model that
                 combines rough set theory (RST), data envelopment
                 analysis (DEA), and genetic programming (GP). Finally,
                 real data-set are used to demonstrate the accuracy of
                 the proposed method.",
  bibsource =    "OAI-PMH server at www.doaj.org",
  language =     "eng",
  oai =          "oai:doaj-articles:601889dc955f0d7b09d556498b97d8da",
}

Genetic Programming entries for Yi-Shian Lee Lee-Ing Tong

Citations