基于模糊支持向量机的智能化体育测试数据完整性检测方法

Intelligent Sports Test Data Integrity Detection Method Based on Fuzzy Support Vector Machine

为了保证智能化体育测试数据的完整性,提出基于模糊支持向量机的智能化体育测试数据完整性检测方法 .通过构建智能化体育测试数据的分布式数据存储结构模型,采用联合自相似性特征解析控制方法对智能化体育测试数据信息交叉融合,获取智能化体育测试数据样本并训练该样本;根据训练结果进行数据离散样本特征聚类,采用量化回归分析方法,提取智能化体育测试数据完整性特征.在此基础上,采用支持向量机方法,进行智能化体育测试数据分类,并以分类结果为基础,用主成分融合和线性相关决策方法,构建智能化体育测试数据完整性检测模型,完成智能化体育测试数据完整性检测.结果表明,基于模糊支持向量机的智能化体育测试数据完整性检测法精度较高,检测时间较短、效率高.

In order to ensure the integrity of intelligent sports test data, an intelligent sports test data integrity detection method based on fuzzy support vector machine is proposed. By constructing the distributed data storage structure model of intelligent sports test data, the joint self similarity feature analytic control method is used to cross fuse the intelligent sports test data information, obtain the intelligent sports test data sample and train the sample;According to the training results, the characteristics of discrete samples were clustered,and the integrity characteristics of intelligent sports test data were extracted by quantitative regression analysis;On this basis, the support vector machine method is used to classify the intelligent sports test data, and based on the classification results, the principal component fusion and linear correlation decision-making methods are used to build an intelligent sports test data integrity detection model to complete the intelligent sports test data integrity detection. The results show that the intelligent sports test data integrity detection method based on fuzzy support vector machine has higher accuracy, shorter detection time and higher efficiency.