A Fuzzy Expert System for Star Classification Based on Photometry
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.
Year of publication: |
2016
|
---|---|
Authors: | Pakniyat, Aida ; Hosseini, Rahil ; Mazinai, Mahdi |
Published in: |
International Journal of Fuzzy System Applications (IJFSA). - IGI Global, ISSN 2156-1761, ZDB-ID 2703297-8. - Vol. 5.2016, 3 (01.07.), p. 109-119
|
Publisher: |
IGI Global |
Subject: | Fuzzy Expert Systems | Fuzzy Set Theory | Harvard Classification | Photometry | Stars Classification |
Saved in:
Online Resource
Saved in favorites
Similar items by subject
-
Artificial Intelligence and fuzzy logic in modern human resource management
Spengler, Thomas, (2023)
-
A technology management strategy selection method for firms in joint venture partnerships
Nakandala, Dilupa, (2015)
-
CALiPER Exploratory Study: Accounting for Uncertainty in Lumen Measurements
Bergman, Rolf, (2011)
- More ...