A New Improved Attribute Weight Algorithm Based on Rough Sets Theory for One Command Information System

Abstract:

There are various evaluation indicators in command information system. It is important to determine the weight of each indicator because it has a direct impact on the final result for evaluation and decision making. The reasonable and accurate attribute weight is helpful to ascertain the status or effect on the policy decision. With analyzing the deficiency of attribute weighting algorithms based on the rough sets theory, the new attribute weight algorithm is proposed in the paper. The proposed algorithm considers objective weight and subjective weight. The objective weight includes three factors, named as the importance of the attribute itself, the increment of mutual information, and its own information entropy. The subjective weight is obtained by the experts with prior knowledge in the field. Experiment results prove that the new method not only overcomes the deficiency of the existing weight methods, but also is more in line with the actual situation.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 2029-2032
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.2029
• Online since: July 2014
• Authors: Su Min Yang*, Ying Min Yan, Kai Wang, Zhi Ying Xie
• Keywords: Attribute Importance, Attribute Weight, Information Entropy, Mutual Information (MI), Rough Set Theory (RST)

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