Changshun Liu1, Yan Liu1, Jingjing Song1,*, Taihua Xu1,2
Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2059-2075, 2023, DOI:10.32604/iasc.2023.039592
Abstract Attribute reduction, as one of the essential applications of the rough set, has attracted extensive attention from scholars. Information granulation is a key step of attribute reduction, and its efficiency has a significant impact on the overall efficiency of attribute reduction. The information granulation of the existing neighborhood rough set models is usually a single layer, and the construction of each information granule needs to search all the samples in the universe, which is inefficient. To fill such gap, a new neighborhood rough set model is proposed, which aims to improve the efficiency of attribute reduction by means of two-layer… More >
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