Detecting Overlapping Areas in Unbalanced High-dimensional Data Using Neighborhood Rough Set and Genetic Programming-Reference-Cited by-同舟云学术

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Detecting Overlapping Areas in Unbalanced High-dimensional Data Using Neighborhood Rough Set and Genetic Programming

Published:2022 Issue: Volume: Page:1-1
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Pei Wenbin¹^ORCID,Xue Bing²^ORCID,Shang Lin³^ORCID,Zhang Mengjie²^ORCID

Affiliation:

1. School of Computer Science and Technology, Dalian University of Technology, Dalian, China

2. School of Engineering and Computer Science, Victoria University of Wellington, PO Box, Wellington, New Zealand

3. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/4358751/09874858.pdf?arnumber=9874858

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Kernel multi-granularity double-quantitative rough set based on ensemble empirical mode decomposition: Application to stock price trends prediction;International Journal of Approximate Reasoning;2024-09

2. Adaptive Key Management-Based Privacy Preservation Protocol for Healthcare Data;Communications in Computer and Information Science;2024

3. A Survey on Unbalanced Classification: How Can Evolutionary Computation Help?;IEEE Transactions on Evolutionary Computation;2023

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