.png){kind=icon}
返回
Precursory Pattern Based Feature Extraction Techniques for Earthquake Prediction
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2902224.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Earthquake prediction is an important and complex task in the real world. Although many data mining-based methods have been proposed to solve this problem, the prediction accuracy is still far from satisfactory due to the deficiency of feature extraction techniques. To this end, in this paper, we propose a precursory pattern-based feature extraction method to enhance the performance of earthquake prediction. Especially, the raw seismic data is firstly divided into fixed day time periods, and the magnitude of the largest earthquake in each fixed time period is labeled as the main shock. The precursory pattern is a part of the seismic sequence before the main shock, on which the existing mathematical statistic features can be directly generated as seismic indicators. Based on these precursory pattern-based features, a simple yet effective classification and regression tree algorithm is adopted to predict the label of the main shock in a predefined future time period. The experimental results on two historical earthquake records of the Changding-Garze and Wudu-Mabian seismic zones of China demonstrate the effectiveness of the proposed precursory pattern-based features with the selected CART algorithm for earthquake prediction.
Keyword:
Earthquake prediction
pattern discovery
time series
precursory pattern
CART
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Earthquake magnitude prediction by adaptive neuro-fuzzy inference system (ANFIS) based on fuzzy C-means algorithm基于模糊C均值算法的自适应神经模糊推理系统 (ANFIS) 地震震级预测.png)
NATURAL HAZARDS
NATURAL HAZARDSIF3.7
PREAI
分享收藏Neural network models for earthquake magnitude prediction using multiple seismicity indicators使用多个地震活动性指标进行地震震级预测的神经网络模型
PREAI
分享收藏分享收藏A simple generalisation of the area under the ROC curve for multiple class classification problems多类分类问题的ROC曲线下面积的简单概括MACHINE LEARNINGOAAI
MACHINE LEARNINGIF2.9
OAAI分享收藏
查看更多内容