Rough Set
A New Method of Translating Covering Rough Set into Classical Rough Set
... Abstract. Binary relational rough sets enrich the applicable scope of classic rough set, but they lose some excellent properties. Therefore, covering translates to partition has become one of the key ...
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BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... This formula denotes the classification quality and feature subset length have different importance. We adopt this approach based on the work done in [10, 23], they states that classification quality is more significance ...
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A Rough Set View on Bayes Theorem
... It is seen clearly from Examples 1 and 2 the difference between Bayesian data analysis and the rough set approach. In the Bayesian inference, the data are used to update prior knowledge (probability) into a ...
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A Variable Precision Fuzzy Rough Set Approach to a Fuzzy Rough Decision Table
... both rough and ...precision rough set) approach is proposed based on substitution of the indiscernibility relation by a fuzzy indiscernibility relation in the rough approximation of decision ...
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Quantization of Rough Set Based Attribute Reduction
... contrast, rough set can hold complete analy- sis, since it considers missing value as “everything is possible” [8, ...9]. Rough set is proposed by Pawlak [10] as a mathematical theory of ...
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Autonomous clustering using rough set theory
... from rough set theory are used to form the ...that rough set theory reflects global data properties, the clustering solution is unaffected by local ...
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Rough Set Approach in Machine Learning: A Review
... a rough set rule induction algorithm generates decision rules, which can reveal profound knowledge and provide new insights ...on rough set theory (PRIMEROSE) and developed a program that ...
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Chikungunya Diagnosing using Rough Set Approach
... Symptoms etc. have been gathered from internet and doctors to identify effective parameters in relation to Chikungunya diagnosis. These attributes shown in Table II. The attributes of age distribution, IgM : IgG ratio, ...
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A Rough Set Formalization of Quantitative Evaluation with Ambiguity
... on rough sets, distinguishing the annotation equivalence relation (in- trinsic criteria) and the reward function (extrinsic criteria), second we presented the notion of potential performance space to describe the ...
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Rough set approach for categorical data clustering
... Therefore, based on these drawbacks, there is a need for improving of those techniques. In this work, a technique termed MDA (Maximum Dependency of Attributes) for categorical data clustering aimed to mine the hidden ...
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Rough Set Based Opinion Mining in Tamil
... the rough set theory is useful to extract the key sentences and its feature attribute after getting the opinion from the post will be ...the rough set theory is used for avoiding the ...
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Fuzzy-Rough Set Bireducts for Data Reduction
... of rough sets is largely the result of a series of desirable theoretical ...traditional rough set theory is that it can only be applied to crisp or discrete-valued ...
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Liquefaction Prediction Using Rough Set Theory
... in rough set analysis in Tables 2(a) and 2(b) are a result of real data from past earthquakes with the same classications as the simplied method proposed by Youd et ...
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Empirical analysis of rough set categorical clustering techniques based on rough purity and value set
... In rough categorical clustering, mainly the data set is expressed as the decision table by introducing a decision ...data set aiming to find a cluster which best represents the data according to some ...
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Retrieving the Missing Information from Information Systems Using Rough Set, Covering Based Rough Set and Soft Set
... Soft set theory has potential applications in many different fields which include the smoothness of functions, game theory, operations research, Riemann integration, Peron integration, probability theory, and ...
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Concept Lattice: A rough set approach
... Concept lattice is an efficient tool for knowledge representation and knowledge discovery and is applied to many fields successfully. However, in many real life applications, the problem under investigation cannot be ...
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BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... Keywords: Permanent Magnet Synchronous Motor PMSM, Modeling and Simulation, Extended Kalman Filter EKF, Vector Control 1... With the development of the power electronics, micro-electroni[r] ...
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BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... After the validation of the trained Fuzzy-ANN model, the study further examined the stock selection capability while applying to the real stock market. The whole sample set was used to generate FIS output. For ...
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BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... In order to mobilize students' learning initiative and active participation, improve the experimental teaching, and reduce the evaluation workload of the experiment, this paper presents [r] ...
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BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... Suppose the initial position is (0m, 0m), the desired position is (10m, 10m). Select the module of Constant as our input and set its value as 10, parameters of PID valued as p=10; i=0.01; d=3. The module of Pid1 ...
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