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Y.-C. Liang, X.-Y. Sun, D.-H. Liu, et al., “Applications of Combinatorial Probabilistic Nural Network in Fault Diagnosis of Power Transformer,” Proceedings of 6th IEEE International Conference on Machine Learning and Cybernetics, Vol. 2, 2007, pp. 1115-1119.

has been cited by the following article:

• TITLE: A Universal Object Oriented Expert System Frame Work for Fault Diagnosis

  AUTHORS: Dattatraya Vishnu Kodavade, Shaila Dinakar Apte

  KEYWORDS: Knowledge; Inference; Object; Microcontroller; Heuristics; Inheritance

  JOURNAL NAME: International Journal of Intelligence Science, Vol.2 No.3, July 27, 2012

  ABSTRACT: The paper presents a universal fault diagnostic expert system frame work. The frame work is characterized by two basic features. The first includes a fault diagnostic strategy which utilizes the fault classification and checks knowledge about unit under test. The degree of accuracy to which faults are located is improved by using fault classification knowledge. The second characteristic is object oriented inference mechanism using message passing. Object orientation in inference mechanism improved inference efficiency. The developed framework demonstrates its effectiveness and superiority compared to earlier approaches using case studies.