Implementation Algorithm of Grey Relational Analysis Application in MATLAB

This article presents the implementation of application algorithms based on Grey Relational Analysis (GRA) in MATLAB. We will first explain the fundamental concepts and principles of grey relational analysis, including its mathematical foundations and practical applications. The implementation section will demonstrate how to prepare data matrices, code the core algorithm using MATLAB's vectorization capabilities, and interpret the resulting relational coefficients. Key implementation aspects include data preprocessing methods (such as normalization using built-in functions like zscore or mapminmax), calculation of grey relational coefficients through matrix operations, and result visualization techniques. We will also discuss the algorithm's advantages in handling incomplete information systems and its limitations in dealing with nonlinear relationships. Potential improvements involving hybrid approaches with machine learning techniques will be explored. The conclusion summarizes key findings and suggests future research directions in optimization and real-time applications. Through this guide, readers will gain comprehensive understanding of GRA principles and practical MATLAB implementation skills for relational analysis tasks.