The invention discloses a sampling GPR method of continuous
anomaly detection in a collecting data flow of an environment sensor, and belongs to the technical field of
data monitoring of environment sensors. The sampling GPR method of the continuous
anomaly detection in the collecting data flow of the environment sensor is used for solving the problem that
anomaly detection can not be conducted in real time, wherein the problem is caused by the fact that data calculation amount is large in data flow anomaly detection of a traditional environment sensor. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor is based on a prediction-
model method, a prediction model is built through historical data, the mean value and the
confidence interval of current data are obtained, a current
data value is compared with the
confidence interval, and the current
data value is regarded as exceptional data if the current
data value exceeds the
confidence interval. According to the sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor, less historical data are needed,
algorithm operation efficiency is improved, and input training data are not required to be provided with category tags. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor can detect an exceptional situation in a self-adaptive mode according to real-time arrival data, and is applied to continuous exceptional
data detection in collecting data flow of the environment sensor.