数据挖掘与数据融合相结合的异类信息融合

Research on the Dissimilar Sensor Fusion Arithmetic Integration of Data Mining and Data Fusion

针对组网系统中的信息样式多、模糊性强等特点,介绍了分布式异类传感器组网系统及其特点,将数据挖掘中的知识发现理论与数据融合的知识应用理论相结合,建立了异类信息综合处理的集成模型。并提出了基于模糊神经网络的数据挖掘算法,增强了集成模型的自学习性能。模型有效地提高了异类传感器组网系统的智能化、自动化能力。

Illuminate the characteristic of distributed dissimilar sensor network, aimed at the multiformity and fuzzy of the information in the network. Combined the knowledge discover theory of data mining and knowledge application theory of data fusion, found the information disposal model of dissimilar input. Advanced data mining arithmetic that swelled the study behavior of integration system based on fuzzy neural network. This modal enhances the intelligent and automatic ability of the dissimilar sensor network.