Entropy Weight Method for Calculating Row/Column Weights and Composite Parameters of Any Matrix

This MATLAB function implements the entropy weight method to calculate row/column weights and composite parameters for any given matrix. The entropy weight method is a multi-criteria decision analysis technique that quantifies the importance of different indicators, providing valuable references for decision-making. This method finds extensive applications across various fields including engineering, environmental science, and economics. The implementation follows a systematic three-step workflow: First, matrix standardization is performed to normalize the data. Second, entropy values and corresponding weights are calculated using probability distributions and logarithmic functions. Finally, composite parameters are obtained by multiplying entropy values with their respective weights. Key implementation aspects include: - Matrix preprocessing and normalization handling - Entropy calculation using Shannon's entropy formula - Weight determination based on information content - Comprehensive parameter computation through matrix operations This approach enables better understanding and analysis of matrix data, facilitating more informed decision-making. The MATLAB implementation provides flexible options for handling both row-wise and column-wise calculations, making it adaptable to various matrix configurations and analytical requirements.