JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2026, Vol. 61 ›› Issue (5): 102-113.doi: 10.6040/j.issn.1671-9352.4.2025.002

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Rotated granular support vector machine classifier algorithm

  

  1. 1. College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, Fujian, China;
    2. Broad Vision(Xiamen)Technology Co., Ltd., Xiamen 361000, Fujian, China;
    3. Fujian Polytechnic Normal University, Fuzhou 350300, Fujian, China
  • Published:2026-05-15

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Abstract: To address the computational complexity challenges of traditional support vector machine on low-dimensional nonlinearly separable and large-scale datasets, a rotated granular support vector machine algorithm is proposed. Based on granular computing theory, rotated granular particles by rotating feature points and forms rotated granular vectors in a multi-plane coordinate system is constructed. Additionally, the size, measurement, and operational rules of the granules are defined. It is demonstrated that the rotated granular support vector machine can effectively handle complexly distributed data with lower computational resource requirements, is efficient and achieves good classification performance.

Key words: support vector machine, granular computing, granular support vector machine, fuzzy sets, loss function

CLC Number: 

  • TP181
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