Research on Model of Seismic Anomaly Data Mining Based on Neural Network
Yancheng Long, Jian Rong · 2021
Data mining in the seismic anomaly database will be affected by the instability of the seismic monitoring system signal and the environment, so in the development of practice should be based on the existing technology to comprehensively explore, pay attention to gradually break through the limitations of traditional mining methods, in order to effectively solve the problems existing in the previous data mining. Under the background of new era, the neural network as a machine learning algorithm is the most common way of mining, need according to the related theory had a clear standard equation of the minimum mean square error values, thus to build optimized mining model, and then using the calculation data of database, the feature vector to construct the corresponding to the monitoring data are accurate judgment. On the basis of understanding the current development of seismic monitoring technology, this paper proposes a new optimization model based on the constructed seismic anomaly database, and verifies its application effect in practice.