改进的粒子群算法在云计算下的数据挖掘中的研究

Research into the Improved Particle Swarm Algorithm in Data Mining of Cloud Computing

云计算中的资源具有实时性、动态性、随机性等特点,传统的数据挖掘方法已经达到满意的预测效果。本文提出了一种基于云计算的数据挖掘方法,首先收集云计算中的数据资源,通过关联规则对其分类,然后将分类后的云计算资源作为学习样本进行支持向量机的输入,利用改进的粒子群算法来选择向量机的最优参数,建立优化的模型。仿真平台说明本文的算法有效的提高云计算下的数据挖掘效果。

Resources in cloud computing are featured by being timely,dynamic and random,andtraditional data mining method has already achieved the satisfactory prediction effect.This paperproposes a data mining method based on cloud computing.First of all,it collects data and resources incloud computing and classifies them through the association rules.Then,it takes the classified cloudcomputing resources as the supporting vector machine for learning,adopts the improved particle swarmalgorithm to choose the optimal parameters and establishes the optimized model.The simulation platformindicates that algorithm in this paper effectively improves the data mining effect in cloud computing.