Wireless sensor high-dimensional data real-time anomaly detection method based on deep learning

Abstract

The invention discloses a wireless sensor high-dimensional data anomaly detection method based on deep learning. The method comprises the following steps: (101) obtaining historical data; (102) establishing a DBN-QSSVM hybrid model; (103) training the mixed model by using historical data of the sensor; (104) collecting test data of a sensor to be detected; (105) using a trained DBN-QSSVM hybrid model in (103) to perform abnormality detection on sensor test data; (106) outputting abnormal data in sensor test data and (106) outputting abnormal data in the sensor test data. Relevant algorithms and processes in the prior art are improved. The method for achieving online detection technology when the high-dimensional data is processed is provided, the space complexity and time complexity can begreatly reduced under the condition that the accuracy of the data exception detection method is not reduced, and therefore the method is more suitable for large-scale high-dimensional data exceptiondetection.

Description

Technical field [0001] The invention relates to the field of wireless sensor abnormal data detection methods, in particular to a real-time abnormal detection method of wireless sensor high-dimensional data based on deep learning. Background technique [0002] With the rapid development of sensor technology, wireless sensor networks are increasingly used in industries such as industry, agriculture, medical care, and health. Among them, the sensor nodes are scattered in the target area, and the environmental parameters (temperature, humidity, CO 2 Concentration, etc.), can monitor the internal environment changes in the scattered area in real time. In order to detect emergencies in the natural environment timely and accurately, monitor the health of the sensor network, and improve the reliability of the wireless sensor network, it is particularly important to detect anomalies in the data collected by the sensors. [0003] Anomaly detection technology is one of the effective means to...

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to provide a real-time anomaly detection method for high-dimensional data of wireless sensors based on deep learning, so as to solve the problem of unsatisfactory detection effect on high-dimensional data and increased Data processing burden, the problem that real-time detection cannot be realized

Images