基于概率分析的云技术Web数据的分类方法研究

发布时间：2018-04-06 03:38

本文选题：概率分析　切入点：云技术　出处：《现代电子技术》2017年16期

【摘要】：为了提高云计算Web数据分类的准确性,针对当前C均值分类的模糊性较大的问题,提出一种基于概率分析的云技术Web数据的分类数学模型构建方法,首先结合数理统计理论建立云技术Web数据分类的状态特征方程,构建Web数据准确分类的边值收敛条件,采用概率随机泛函进行云技术Web数据分类的稳定特征优化解求解,然后在有限论域内实现Web数据准确分类的置信区间准确计算,实现数据有效分类。最后进行仿真分析,结果表明,采用该文方法进行云技术Web数据分类的准确性较好、置信度较高。
[Abstract]:In order to improve the accuracy of cloud computing Web data classification, a mathematical model of cloud Web data classification based on probability analysis is proposed.Firstly, the state characteristic equation of cloud Web data classification is established based on mathematical statistics theory, and the boundary value convergence condition for accurate classification of Web data is constructed. The stable feature optimization solution of cloud Web data classification is solved by using probabilistic stochastic functional.Then, the confidence interval of accurate classification of Web data is calculated in finite theory domain, and the effective classification of data is realized.Finally, the simulation results show that the proposed method is accurate and reliable for cloud Web data classification.
【作者单位】：河池学院计算机与信息工程学院;
【基金】：国家自然科学基金项目(11561019)
【分类号】：TP3

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