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Energies 2012, 5(3), 545-560; doi:10.3390/en5030545
Article

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

1,*  and 2
Received: 24 January 2012; in revised form: 13 February 2012 / Accepted: 20 February 2012 / Published: 27 February 2012
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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 utilized to demonstrate the accuracy of the proposed method.
Keywords: photovoltaic systems; rough set theory; data envelopment analysis; genetic programming; hybrid model photovoltaic systems; rough set theory; data envelopment analysis; genetic programming; hybrid model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Lee, Y.-S.; Tong, L.-I. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming. Energies 2012, 5, 545-560.

AMA Style

Lee Y-S, Tong L-I. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming. Energies. 2012; 5(3):545-560.

Chicago/Turabian Style

Lee, Yi-Shian; Tong, Lee-Ing. 2012. "Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming." Energies 5, no. 3: 545-560.


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