MATLAB Implementation of Grey Relational Analysis

The MATLAB implementation of grey relational analysis provides an effective approach for data analysis and decision support. This method calculates correlation degrees between different data dimensions through algorithmic processing, enabling quantitative assessment of inter-dimensional relationships. Key implementation steps include data normalization using functions like zscore or mapminmax, calculating grey relational coefficients through element-wise operations, and determining relational degrees via weighted averaging. The technique proves particularly valuable for analyzing relationships between time series or spatial sequences, with MATLAB's matrix operations (e.g., bsxfun for efficient broadcasting) facilitating rapid computation of large datasets. With broad applicability in economic forecasting, environmental monitoring, and medical research, this MATLAB-based implementation offers a robust methodology worth promoting for data-driven decision support systems. The code typically involves correlation coefficient matrices computed using vectorized operations and includes visualization components like plot functions for result interpretation.