Multiagent-consensus-MapReduce-based attribute reduction using co-evolutionary quantum PSO for big data applications-Reference-Cited by-同舟云学术

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Multiagent-consensus-MapReduce-based attribute reduction using co-evolutionary quantum PSO for big data applications

Published:2018-01 Issue: Volume:272 Page:136-153
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Ding Weiping,Lin Chin-Teng,Chen Senbo,Zhang Xiaofeng,Hu Bin

Funder

National Natural Science Foundation of China

Nanjing University

Natural Science Foundation of Jiangsu Province

Six Talent Peaks Project of Jiangsu Province

Applied Basic Research Program of Nantong

Jiangsu Provincial Government Scholarship Program

Jilin University

Ministry of Education

Jiangsu Provincial Key Laboratory of Computer Information Processing Technology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference40 articles.

1. Data-intensive applications, challenges, techniques and technologies: a survey on big data;Chen;Inf. Sci.,2014

2. Anonymizing classification data using rough set theory;Ye;Knowl. Based Syst.,2013

3. A hierarchical-coevolutionary-MapReduce-based knowledge reduction algorithm with robust ensemble Pareto equilibrum;Ding;Inf. Sci.,2016

4. Tolerance rough sets for pattern classification using multiple grey single-layer perceptrons;Hu;Neurocomputing,2016

5. A more efficient attribute self-adaptive co-evolutionary reduction algorithm by combining quantum elitist frogs and cloud model operators;Ding;Inf. Sci.,2015

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