Study on Pattern Recognition and Optimization of Improved Iterative Matrix in Petroleum Geology Based on Machine Learning

Authors

  • Jianqiang Liu

Abstract

Along with the progress of human society and constantly improve the level of science and technology, today's social production and living of the degree of dependence on computer Improved Iterative Matrix in Petroleum Geology is becoming more and more high, the number of Internet users has been more and more, the amount of data on the Internet also has increased dramatically, society has step into the era of  Improved Iterative Matrix in Petroleum Geology, and the large number of very large data in the data and the complexity of the data sets need professional analysis tool. In this paper, a correlation analysis technique for content analysis of Improved Iterative Matrix in Petroleum Geology is proposed, which makes use of the optimal linear fitting regression of many independent variables. In order to verify the performance of the proposed algorithm, discrete point plotting and optimal linear regression are used. The results show that, after the implementation of CAM, the correlation coefficient between the math test score and the extended knowledge test score is calculated as 0.5235423. The results show that there is a positive correlation between math test scores and knowledge expansion test scores, and the two variables increase with the increase of one variable.

Published

2020-11-01

Issue

Section

Articles