Researchers have put forward variety of knowledge acquisition methods for automatic learning of the rule-based systems. It has been suggested that two basic anomalies of rule-based system are incompleteness and incorrectness. In the chapter, a fuzzy rule-based system has been presented that not only self-learns and self-corrects but also self-expands. The chapter moves ahead with description of the configuration of the system, followed by explanation of the methodology that consists of algorithms for different modules. At the end, the operation of the self-progressing fuzzy rule-based system is explained with the help of examples related to optimization of machining process.
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Iqbal, A., Dar, N.U. (2009). A Self Progressing Fuzzy Rule-Based System for Optimizing and Predicting Machining Process. In: Ao, SI., Gelman, L. (eds) Advances in Electrical Engineering and Computational Science. Lecture Notes in Electrical Engineering, vol 39. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2311-7_37
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