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International Conference on Knowledge-Based and Intelligent Information and Engineering Systems

KES 2006: Knowledge-Based Intelligent Information and Engineering Systems pp 387–392Cite as

Prediction of Electric Power Generation of Solar Cell Using the Neural Network

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4252))

Abstract

We proposed the prediction system of electric power generation of solar cell using neural network. Recently, the solar cell system is developing in many fields. However this system is easily to influence by the weather condition. In the practical application, it has been required the prediction of electric power generation. By this system, it is possible to make the planning of supply and the security of alternative power source. This prediction system is used neural network system and it can predict the integral power consumption, largest electric power and time-serial prediction.

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References

  1. Yamamoto, S., Park, J.S., Takata, M., Sasaki, K., Hashimoto, T.: Basic study on the prediction of solar irradiation and its application to photovoltaic-diesel hybrid generation system. Journal of Solar Energy Materials & Solar Cells 75(3–4), 577–584 (2003)

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  2. Rumellhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation, Parallel distributed processing, pp. 318–362. MIT Press, Cambridge (1986)

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  3. Ichikawa, S., Kawaguchi, M., Okuno, M.: Measurement and Prediction of Electric Power Generation of Solar Cell Using the Neural Network, Record of Tokai-Section Joint Conference of the Eight Institutes of Electrical and Relater Engineers, 34 (2003)

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Author information

Authors and Affiliations

  1. Department of Electrical & Electronic Engineering, Suzuka National College of Technology, Shiroko, Suzuka, Mie, 510-0294, Japan

    Masashi Kawaguchi, Sachiyoshi Ichikawa & Masaaki Okuno

  2. Department of Environmental Technology and Urban Planning Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan

    Takashi Jimbo

  3. Department of Information Network Engineering, Aichi Institute of Technology, Yachigusa, Yagusa-cho, Toyota, 470-0356, Japan

    Naohiro Ishii

Authors
  1. Masashi Kawaguchi
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  2. Sachiyoshi Ichikawa
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  3. Masaaki Okuno
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  4. Takashi Jimbo
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  5. Naohiro Ishii
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kawaguchi, M., Ichikawa, S., Okuno, M., Jimbo, T., Ishii, N. (2006). Prediction of Electric Power Generation of Solar Cell Using the Neural Network. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_50

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  • DOI: https://doi.org/10.1007/11893004_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46537-9

  • Online ISBN: 978-3-540-46539-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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