Neighborhood multi-granulation rough sets-based attribute reduction using Lebesgue and entropy measures in incomplete neighborhood decision systems-Reference-Cited by-同舟云学术

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Neighborhood multi-granulation rough sets-based attribute reduction using Lebesgue and entropy measures in incomplete neighborhood decision systems

Published:2020-03 Issue: Volume:192 Page:105373
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Sun Lin,Wang Lanying,Ding Weiping,Qian Yuhua,Xu Jiucheng

Funder

National Natural Science Foundation of China

Plan for Scientific Innovation Talent of Henan Province, China

Key Scientific and Technological Project of Henan Province, China

Young Scholar Program of Henan Province, China

Natural Science Foundation of Jiangsu Province, China

Six Talent Peaks Project of Jiangsu Province, China

Qing Lan Project of Jiangsu Province, China

Natural Science Foundation of Henan Province, China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference70 articles.

1. Deep neuro-cognitive co-evolution for fuzzy attribute reduction by quantum leaping PSO with nearest-neighbor memeplexes;Ding;IEEE Trans. Cybern.,2019

2. Feature selection using neighborhood entropy-based uncertainty measures for gene expression data classification;Sun;Inform. Sci.,2019

3. A layered-coevolution-based attribute-boosted reduction using adaptive quantum behavior PSO and its consistent segmentation for neonates brain tissue;Ding;IEEE Trans. Fuzzy Syst.,2018

4. Multi-granulation entropy and its applications;Zeng;Entropy,2013

5. Feature selection via neighborhood multi-granulation fusion;Lin;Knowl.-Based Syst.,2014

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