Taguchi approach and decision tree algorithm for prediction of wear rate in zinc oxide-filled AA7075 matrix composites
Author:
Publisher
IOP Publishing
Subject
Materials Chemistry,Surfaces, Coatings and Films,Process Chemistry and Technology,Instrumentation
Link
https://iopscience.iop.org/article/10.1088/2051-672X/ac0f34/pdf
Reference28 articles.
1. A datamining approach to classify, select and predict the formation enthalpy for intermetallic compound hydrides;Djellouli;Int. J. Hydrogen Energy,2018
2. The data mining industry coming of age;Piatetsky Shapiro G;IEEE Intell. Syst.,1999
3. An integrated data mining model for manufacturing enterprises;Shahbaz,2003
4. From data to big data in production research: the past and future trends;Kuo;Int. J. Prod. Res.,2019
5. A data mining in manufacturing: a review;Harding;J. Manuf. Sci. Eng.,2018
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