Research on Earthquake Data Processing and Abnormality Detection Based on Deep Learning
Earthquake data processing and abnormality detection are crucial steps in earthquake prediction,and their accuracy directly affects the reliability of prediction results.This study utilizes deep learning technology to conduct in-depth exploration of earthquake data processing and abnormality detection.By analyzing the characteristics of earthquake data,a preprocessing method based on deep learning is proposed,which significantly improves data quality and processing efficiency.Furthermore,an abnormality detection model based on deep learning is constructed,which can automatically learn data characteristics and accurately identify abnormal information in earthquake data,thus improving the accuracy of abnormality detection.Comparative experiments show that the method proposed in this study has significant advantages compared with traditional methods,effectively improving the accuracy of earthquake prediction.The research results have important reference value for enhancing China's earthquake warning capability and reducing earthquake disaster losses.
deep learningearthquake data processingabnormality detectionearthquake predictionearthquake warning capability
万方数据
维普
