Based on fuzzy neural network of multi-agent data fusion
Based on fuzzy neural network of multi-agent data fusion
复制标题
基于模糊神经网络的多智能体数据融合
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Tongying Guo
中科院分区：
文献类型：
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作者：
Bin Ma;Nannan Li;Changtao Wang;Zhonghua Han;Tongying Guo
模糊神经网络在多传感器数据融合中有着广泛的应用。本设计基于传感器级数据融合，然后利用多代理中间件实现二次数据融合。目的是解决多传感器数据融合中提供的信息不准确、不完整、模糊甚至矛盾的不确定性。层次融合采用模糊神经网络ANFIS结构，获得较好的精度。以建筑环境中的智能火灾探测为例，证明了多智能体数据融合的有效性和可行性。
Fuzzy neural network in multi-sensor data fusion has a wide range of applications. This design based on the sensor level data fusion, then the use of multi-agent middleware to achieve secondary data fusion. Aim to solve a multi-sensor data fusion provide information inaccurate, incomplete, ambiguous or even contradictory uncertainty. Levels of fusion using fuzzy neural network ANFIS structure to obtain better accuracy. Take intelligent fire detection in the built environment for example, proved the effectiveness and feasibility of the multi-agent data fusion.