Data-Driven Interval Granulation Approach Based on Uncertainty Principle for Efficient Classification

Wu, Chengying; Zhang, Qinghua; Yin, Longjun; Quan, Xie; Luo, Nanfang; Wang, Guoyin

doi:10.1109/tfuzz.2023.3287834

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2024

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“…The time complexity of ISPAN is O( n+m q ). Granular computing (GrC) [18][19][20][21][22][23] is a methodology for viewing the objective world. It abstracts and divides a complex problem into simple problems.…”

Section: Introductionmentioning

confidence: 99%

A Granulation Strategy-Based Algorithm for Computing Strongly Connected Components in Parallel

He,

Xu,

Chen

et al. 2024

Mathematics

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Granular computing (GrC) is a methodology for reducing the complexity of problem solving and includes two basic aspects: granulation and granular-based computing. Strongly connected components (SCCs) are a significant subgraph structure in digraphs. In this paper, two new granulation strategies were devised to improve the efficiency of computing SCCs. Firstly, four SCC correlations between the vertices were found, which can be divided into two classes. Secondly, two granulation strategies were designed based on correlations between two classes of SCCs. Thirdly, according to the characteristics of the granulation results, the parallelization of computing SCCs was realized. Finally, a parallel algorithm based on granulation strategy for computing SCCs of simple digraphs named GPSCC was proposed. Experimental results show that GPSCC performs with higher computational efficiency than algorithms.

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