基于Kalman滤波的Web数据流抗干扰挖掘算法

Anti Interference Mining of Web Data Stream Based on Kalman Filtering

提出一种基于变维Kalman滤波的Web海量数据流抗干扰挖掘算法。构建Web环境下的海量数据挖掘数据流信息模型和噪声干扰模型,结合现代信号处理方法,设计变维Kalman滤波算法进行海量数据流信号滤波预处理,把Web海量数据流映射为一组非线性宽带调频信号模型,采用信号检测算法实现Web海量数据的抗干扰挖掘。仿真结果表明,采用该算法进行Web海量数据信息的抗干扰挖掘,具有较高的数据检测精度和准确挖掘性能,具有较高的抗干扰性和鲁棒性。

An anti jamming mining algorithm for Web massive data stream based on the variable dimension Kalman filter-ing is proposed.. Construct the massive amount of data in the web data mining information flow model and noise model, com-bined with modern signal processing methods to design the variable dimension Kalman filtering algorithm of massive data flow signal filtering pre processing, the web massive data flow is mapped to a set of nonlinear wideband FM signal model and uses the signal detection algorithm is to achieve a large amount of Web data anti-interference mining. Simulation re-sults show that by using the algorithm of Web data information of magnanimity anti-interference mining, it has higher preci-sion of measured data and accurate mining performance and has high anti-interference and robustness.