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A Fuzzy Expert System for Star Classification Based on Photometry

Author

Listed:
  • Aida Pakniyat

    (Department of Computer Science, Kharazmi University, Tehran, Iran)

  • Rahil Hosseini

    (Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran)

  • Mahdi Mazinai

    (Department of Electrical Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran)

Abstract

The application of fuzzy systems is emerging in science where experts' knowledge plays a vital role. This paper utilizes the capability of fuzzy set theory for managing uncertainty associated to star classification problem. The fuzzy classifies uses a dataset of stars obtained from Harvard classification. This paper, for the first time, presents fuzzy starts classification based on photometry. For performance evaluation, an ROC analysis was performed. The results reveal a classifier with an accuracy of 83.5% and with the 72% area under the ROC curve. The mean square error (MSE) was ?3.77*10?^(-5) which reveals superiority of the proposed fuzzy expert system compared to the other classification methods.

Suggested Citation

  • Aida Pakniyat & Rahil Hosseini & Mahdi Mazinai, 2016. "A Fuzzy Expert System for Star Classification Based on Photometry," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 5(3), pages 109-119, July.
    • Handle: RePEc:igg:jfsa00:v:5:y:2016:i:3:p:109-119
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