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Hybrid Rough Sets and Applications in Uncertain Decision-Making - Lirong Jian

Hybrid Rough Sets and Applications in Uncertain Decision-Making

By: Lirong Jian, Sifeng Liu, Yi Lin

eText | 7 September 2010 | Edition Number 1

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As a powerful approach to data reasoning, rough set theory has proven to be invaluable in knowledge acquisition, decision analysis and forecasting, and knowledge discovery. With the ability to enhance the advantages of other soft technology theories, hybrid rough set theory is quickly emerging as a method of choice for decision making under uncertain conditions.

  • Addresses the variety of uncertainties that can arise in the practical application of knowledge representation systems
  • Unveils a novel hybrid model of probability and rough sets
  • Introduces grey variable precision rough set models
  • Analyzes the advantages and disadvantages of various practical applications

The authors examine the scope of application of the rough set theory and discuss how the combination of variable precision rough sets and dominance relations can produce probabilistic preference rules out of preference attribute decision tables of preference actions. Complete with numerous cases that illustrate the specific application of hybrid methods, the text adopts the latest achievements in the theory, method, and application of rough sets.

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Published: 10th September 2018

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