Applying modifiers to knowledge acquisition
Information Sciences—Informatics and Computer Science: An International Journal - Special issue computing with words
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Journal of Computer Science and Technology
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CHI '00 Extended Abstracts on Human Factors in Computing Systems
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IEEE Transactions on Knowledge and Data Engineering
Knowledge Acquisition Based on Rough Set Theory and Principal Component Analysis
IEEE Intelligent Systems
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Decision Support Systems
Approximation spaces in off-policy Monte Carlo learning
Engineering Applications of Artificial Intelligence
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Converse approximation and rule extraction from decision tables in rough set theory
Computers & Mathematics with Applications
A complex projection scheme and applications
Computers & Mathematics with Applications
Fuzzy-Rough Sets Assisted Attribute Selection
IEEE Transactions on Fuzzy Systems
Two-aircraft formation flight simulation system based on four-tiered architecture
Computers & Mathematics with Applications
A hybrid approach to outlier detection based on boundary region
Pattern Recognition Letters
Dominance-based rough set model in intuitionistic fuzzy information systems
Knowledge-Based Systems
Information Sciences: an International Journal
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Rough Set reduction is a typical iterative process; however, the user cannot give extra controls and preferences during the consecutively iterative process. In this paper, we propose a novel approach to Rough Set reduction by using control science viewpoint. In this model, information system is regarded as controlled plant, user's preference about attributes is regarded as control objective, and the iterative algorithm designing process is regarded as control law designing. We have investigated the properties of Rough Set reduction based on control approach, and have designed the control system based on the properties, where single attribute set and user specified attributes are all used as core attributes to control a pruning process, and other core attributes worked out by previous steps are also used, iteratively. Such that it forms a dynamic closed-loop control by which the user can give much more interactivities. We have also implemented the experimental platform, and the experimental results show that the proposed approach is efficient and effective.