基于模糊逻辑支持向量机(PSO-SVM)算法及计算机应用的图数据库相似度搜索

Tao Yu, Feng He
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引用次数: 1

摘要

支持向量机(SVM)具有优异的学习性能,已成为机器学习领域的热门研究方法,并已成功应用于多个领域。近年来,相关学者提出了越来越多的建模方法来解决分类识别、风险预测、有效性评价等问题。本文简要介绍了支持向量机(SVM),阐述了支持向量机在图数据库相似度搜索中的算法及计算机应用,供读者参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Similarity search of graph database based on Fuzzy Logic Support vector machine (PSO-SVM) algorithm and computer application
Support vector machine (SVM) has excellent learning performance, has become a popular research method in the field of machine learning, and has been successfully applied in many fields. In recent years, more and more modeling methods have been put forward by relevant scholars to solve problems such as classification identification, risk prediction, and effectiveness evaluation. This article briefly introduces the support vector machine (SVM), and expounds the algorithm of support vector machine in graph database similarity search and computer application for readers’ reference.
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