Omkar, SN and Senthilnath, J and Suresh, S (2009) Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques. In: Indian journal of engineering and materials sciences, 16 (4). pp. 205-210.
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In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.
|Item Type:||Journal Article|
|Additional Information:||copyright of this article belongs to National Institute of Science Communication and Information Resources.|
|Keywords:||Tool wear monitoring;Genetic Programming;Ant-Miner.|
|Department/Centre:||Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)|
|Date Deposited:||12 Jan 2010 08:02|
|Last Modified:||19 Sep 2010 05:53|
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