Inside Case-Based Reasoning
Rough sets and intelligent data analysis
Information Sciences—Informatics and Computer Science: An International Journal
A case-based reasoning system for PCB principal process parameter identification
Expert Systems with Applications: An International Journal
Developing a business failure prediction model via RST, GRA and CBR
Expert Systems with Applications: An International Journal
Rough set-based heuristic hybrid recognizer and its application in fault diagnosis
Expert Systems with Applications: An International Journal
A rough set-based case-based reasoner for text categorization
International Journal of Approximate Reasoning
Creep feed grinding optimization by an integrated GA-NN system
Journal of Intelligent Manufacturing
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Case Based Reasoning (CBR) is a novel paradigm that uses previous cases to solve new, unseen and different problems. However, redundant features may not only dramatically increase the case memory, but also make the case retrieval more time-consuming. Furthermore, camshaft grinding process is controlled by a number of process parameters, and it is more complex comparing with the ordinary cylindrical grinding. The process conditions are achieved by skilled and professional workers. Therefore, this research combines Rough set (RS) and CBR for process conditions selection in camshaft grinding, and Genetic Algorithm (GA) is developed to discretize condition features. Through the approach an optimal subset of process conditions can be selected quickly and effectively from a large database with a lot of cases, and complexity of computation of the similarity testing is significantly reduced. Moreover, the validity of the proposed solution is verified by the application of practical experiments for the process conditions selection in camshaft grinding.