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汽车防盗系统本身具有复杂性和多变性等特点,一般的汽车防盗装置大多只使用单一的传感器,单个传感器不能为防盗的决策控制提供准确的依据。选择多种传感器建立的汽车防盗系统,运用多传感器融合技术,采用模糊神经网络技术进行信息融合,对汽车被盗信息进行多方面地监测,从而获得较为可靠的信息,为准确地判断汽车的状态提供依据,具有较强的决策控制能力,达到了准确预警的目的。
Auto anti-theft system itself has the characteristics of complexity and variability, the general car anti-theft devices are mostly used only a single sensor, a single sensor can not provide an accurate basis for the anti-theft decision-making control. Select a variety of sensors to establish the car alarm system, the use of multi-sensor fusion technology, the use of fuzzy neural network technology for information fusion, multi-faceted monitoring of car theft information, in order to obtain more reliable information to accurately determine the status of the car Provide the basis for a strong decision-making ability to control, to achieve the purpose of accurate warning.