智能设备网络虚假信息行为识别与控制技术研究

传统智能设备网络虚假信息行为识别技术识别范围小，准确性低，在识别后不能快速地采取控制手段进行控制，导致事态进一步恶化。针对上述问题，研究了一种新的智能设备网络虚假信息行为识别与控制技术，设定虚假信息模型，由神经网络和BP网络构成，通过互联网控制，通过检测触发词、信息分类、虚假信息识别完成精确识别工作，控制模型由演示平台、网络中心组成，能够针对不同类型的虚假信息给出不同的控制手段。与传统技术进行实验研究，结果表明，给出的智能设备网络虚假信息行为识别技术能够完成更大范围的识别，提高识别准确率，在识别后对应的控制技术会快速采取有效手段控制虚假信息的散布。

Research on False Information Behavior Recognition and Control Technology in Intelligent Device Network

The traditional intelligent device network false information behavior recognition technology has a small recognition range and low accuracy. It cannot be quickly controlled by control after identification, which leads to further deterioration of the situation. Aiming at the above problems, this paper studies a new intelligent device network false information behavior recognition and control technology, and sets up a false information model, which is composed of neural network and BP network. It is controlled by the Internet and detects trigger words, information classification and false information. The precise identification work is completed. The control model is composed of a demonstration platform and a network center, and can provide different control means for different types of false information. Experimental research with traditional techniques shows that the intelligent information network false information behavior recognition technology can complete a wider range of recognition and improve the recognition accuracy. After the identification, the corresponding control technology will quickly take effective measures to control the false information. spread.