MATLAB Implementation of Dempster-Shafer Evidence Theory

This document presents a MATLAB implementation of Dempster-Shafer (DS) Evidence Theory, a fundamental framework in data mining particularly valuable for fault diagnosis systems. Beyond fault diagnosis applications, DS evidence theory finds extensive utility in pattern recognition, decision analysis, and intelligent systems development. The MATLAB implementation includes key algorithmic components such as mass function assignment, belief and plausibility calculations, and Dempster's combination rule for evidence fusion. Through this MATLAB implementation, researchers and practitioners can efficiently conduct data mining experiments and develop evidence-based reasoning systems. The code typically involves functions for handling uncertainty management, conflict resolution between evidence sources, and decision-making under incomplete information. This documentation provides detailed insights into DS evidence theory fundamentals and its practical application in fault diagnosis scenarios, complete with MATLAB code examples demonstrating evidence combination and uncertainty quantification techniques.