Attributes reduction and rules acquisition in an lattice-valued information system with fuzzy decision

2016 ◽  
Vol 8 (1) ◽  
pp. 135-147 ◽  
Author(s):  
Xiaoyan Zhang ◽  
Ling Wei ◽  
Weihua Xu
Keyword(s):  
Information System ◽  
Fuzzy Decision ◽  
Rules Acquisition

Rule Acquisition Based on Inconsistent Decision-Making Information System

2013 ◽  
Vol 411-414 ◽  
pp. 1975-1978
Author(s):  
De Xing Wang ◽  
Hong Yan Lu ◽  
Hong Wei Lu
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Rough Set Theory ◽  
Decision Rules ◽  
Knowledge Reduction ◽  
Inconsistent Information ◽  
Rule Acquisition ◽  
Theory Application ◽  
Rules Acquisition

Rule acquisition is a hot topic in the field of data mining. And the inconsistent information systems are widespread nowadays. However, rules acquisition methods are always the difficulty of rough set theory application in inconsistent decision information systems; So the paper proposes a new rule acquisition method. Firstly, we use maximum distribution reduction method for knowledge reduction in single decision-making inconsistent information system and then we use decision-making resolution matrix and decision-making matrix function to get the decision rules. Finally, we mine the rules from inconsistent decision-making information systems.

scholarly journals Decision Rules Acquisition for Inconsistent Disjunctive Set-Valued Ordered Decision Information Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hongkai Wang ◽  
Yanyong Guan ◽  
Jilin Huang ◽  
Jianting Shen
Keyword(s):  
Information System ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Decision Rules ◽  
Optimal Decision ◽  
Formal Framework ◽  
Rules Acquisition

Set-valued information system is an important formal framework for the development of decision support systems. We focus on the decision rules acquisition for the inconsistent disjunctive set-valued ordered decision information system in this paper. In order to derive optimal decision rules for an inconsistent disjunctive set-valued ordered decision information system, we define the concept of reduct of an object. By constructing the dominance discernibility function for an object, we compute reducts of the object via utilizing Boolean reasoning techniques, and then the corresponding optimal decision rules are induced. Finally, we discuss the certain reduct of the inconsistent disjunctive set-valued ordered decision information system, which can be used to simplify all certain decision rules as much as possible.

Research of Logical Reasoning and Application Based on Granular Computing Rough Sets

2012 ◽  
Vol 622-623 ◽  
pp. 1877-1881
Author(s):  
Wei Wang ◽  
Sheng Wu Xiong
Keyword(s):  
Granular Computing ◽  
Disease Diagnosis ◽  
Logical Reasoning ◽  
Fish Disease ◽  
Fuzzy Decision ◽  
Disease Symptoms ◽  
Information Granule ◽  
Theory Application ◽  
System Uncertainties ◽  
Rules Acquisition

In this paper, the information granule based on granular computing is discussed, the granular computing formula of IS (Information System) uncertainties reasoning based Rough and its processes have been proposed. The fish disease diagnostic information data are fuzziness, randomness and uncertainties in the field of aquaculture. The logical reasoning algorithms are described using fuzzy decision table, which is composed of the condition attributes granules formed by the fish disease symptoms sets and decision granules formed by the fish diseases sets. This method is that fish disease diagnostic rules acquisition process, not only can promote the development of granular computing theory application, but also provide a new method for fish disease diagnosis.

Research on Knowledge Change Rate-Based Attribute Importance Measure Method

2015 ◽  
Vol 713-715 ◽  
pp. 628-632
Author(s):  
Fa Chao Li ◽  
Qi Hui Hu
Keyword(s):  
Information System ◽  
Information Fusion ◽  
Comprehensive Evaluation ◽  
Importance Measure ◽  
Fuzzy Decision ◽  
Attribute Importance ◽  
Change Rate ◽  
Broad Application ◽  
Upper Approximation ◽  
Knowledge Change

For the problem of attribute importance measure, basing on the decision information system, and according to the characteristics and shortcomings of the existing measure modes, we discussed the associated features between the lower and upper approximation of decision classes and the knowledge in system. Then, we constructed an attribute importance measure mode based on the knowledge change rate, and analyzed the features of the constructing measure mode from different angles. Theoretical analysis and example calculation show that the established mode is a supplement and perfect for the existing measure modes, and it not only can effectively use the existed information to reveal the associated features among each attribute, but also have a good structural characteristic and strong interpretability. It has a broad application prospect among information fusion, fuzzy decision, comprehensive evaluation and so on.

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