Improved Approach Based on Fuzzy Rough Set and Sine-Cosine Algorithm: A Case Study on Prediction of Osteoporosis

Ewees, Ahmed A.; Elaziz, Mohamed Abd; Arafa, Rasha M.; Ghoniem, Rania M.

doi:10.1109/access.2020.3036831

Cited by 1 publication

(1 citation statement)

References 62 publications

(63 reference statements)

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“…After Zadeh [1] introduced fuzzy sets, some fuzzy sets methods have been introduced to deal with some nonlinear relationships. Although some papers [2], [3] introduced that fuzzy rough set methods can be directly applied to continuous data, they basically refer to the input continuous data, when the output data is continuous, they always have the continuous output data discretized and classified first, and transform the problem to the classification problem, however, this process would result in information loss and errors [3]- [5]. In information systems, the main goal of the attribute reduction classification methods is to remove redundant information, so that a correct decision can quickly be made while preserving or even improving the classification ability [6].…”

Section: Introductionmentioning

confidence: 99%

A Novel Fuzzy Monotone Relationship Method With its Application on Inclusion Degree

Liang

Zhang

2022

IEEE Access

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This paper introduces a new fuzzy monotone relationship and its associated method, which are applied to feature selection and correlation analysis. Specifically, after the concept of a fuzzy monotone is introduced, this paper first defines a new fuzzy monotone relationship between inputs and output. Second, a fuzzy inclusive monotone model is constructed on inclusion degree through several proved propositions, together with presenting a fuzzy inclusive monotone decision membership function. Third, a new algorithm is developed according to the proposed model for feature selection or correlation analysis. Compared with several methods, the proposed algorithm has been validated on several data sets. The results indicate that the proposed algorithm is effective for the selection of numeric attributes, and the correlation analysis. The novel fuzzy monotone relationship and the method are validated through theoretic proof and experimental results.

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