Inference and learning methodology of belief-rule-based expert system for pipeline leak detection

A sequential learning algorithm for online constructing belief-rule-based systems

A belief rule base inference methodology using the evidential reasoning (RIMER) approach has been developed recently. A belief rule base (BRB), which can be treated as a more generalized expert system, extends traditional IF-THEN rules, but requires the assignment of some system parameters including rule weights, attribute weights, and belief degrees. These parameters need to be determined with...

Bayesian reasoning approach based recursive algorithm for online updating belief rule based expert system of pipeline leak detection

Online updating belief rule based system for pipeline leak detection under expert intervention

Online Fault Detection and Isolation Method Based on Belief Rule Base for Industrial Gas Turbines

Real time and accurate fault detection has attracted an increasing attention with a growing demand for higher operational efficiency and safety of industrial gas turbines as complex engineering systems. Current methods based on condition monitoring data have drawbacks in using both expert knowledge and quantitative information for detecting faults. On account of this reason, this paper proposes...

Edge Detection Based On Nearest Neighbor Linear Cellular Automata Rules and Fuzzy Rule Based System

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...