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。
In order to improve the accuracy of cloud computing Web data classification, in allusion to the fuzzification of C means classification, a method of constructing the probability analysis based classification mathematical model of cloud technology Web data is put forward. The state feature equation of cloud technology Web data classification is established according to the mathematical statistics theory. The boundary value convergence condition of accurate classification of Web data is built, probability random functional is used to solve stable feature optimization solution of cloud technology Web data classification, and then realize the Web data classification calculation at confidence interval in finite domain and implement the effective data classification. The simulation analysis results show that the method has high accuracy and high confidence coefficient for cloud technology Web data classification.
出处
《现代电子技术》
北大核心
2017年第16期41-43,共3页
Modern Electronics Technique
基金
国家自然科学基金项目(11561019)
关键词
概率分析
云技术
Web数据
数据分类
probability analysis
cloud technology
Web data
data classification
