Research on Database Failure Prediction Based on Deep Learning Model

2018 3rd International Conference on Insulating Materials, Material Application and Electrical Engineering

材料科学;无线电电子学;电工学

Zhang, Mingming^1 ; Chen, Zhigang^1 ; Wang, Huiyu^1 ; Zeng, Zeng^1 ; Shan, Xinwen^1

State Grid Jiangsu Electric Power Company Information and Communication Branch, Nanjing, China^1

关键词: Analysis strategies;    Effective management;    Failure prediction;    Feature learning;    Operation and maintenance;    Prediction algorithms;    Prediction model;    Prediction performance;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/452/3/032056/pdf
DOI  :  10.1088/1757-899X/452/3/032056

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Effective management of the database plays an important role in the development of the grid business and the reduction of operation and maintenance costs. For the oracle database, there are many factors affecting its performance. It is difficult for the oracle database to predict possilble problems with the common method. This paper proposes an analysis strategy based on oracle AWR report. By introducing a self-encoding deep learning model to construct a database failure prediction mechanism. The experiment shows that the failuture prediction model of this method has better prediction performance than the prediction algorithm with omitted feature learning.