A Comparison Between Correlation and Grey Relational for Big Data and Analytics

Abstract

Recently, several methods to find similarity of data format and correlation between data and signal have been used for solving correlation of these things. The disadvantages of the methods are spent period of processing time, which are not suitable for large quantities of data. The objectives of this study were: 1) to review correlation and grey relational algorithm, 2) to compare between Pearson correlation coefficient and grey relational analysis, and 3) to examine experimental data for big data and analytics. Comparisons between grey relational and correlation function were used in MATLAB. Result of an analysis dedicated that three factors of the study follow: 1) period of processing time, 2) value of similarities, and 3) accuracy of information. The findings suggest that grey relational analysis takes the time to process less than correlation and more appropriate of the development and growth of Internet of Things.