Optimization of Process Parameters of Abrasive Water Jet Machining Using Variations of Cohort Intelligence (CI)
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-13-1822-1_43
Reference9 articles.
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2. Kechagias, J., Petropoulos, G., Vaxevanidis, N.: Application of Taguchi design for quality characterization of AWJM of TRIP sheet steels. Int. J. Adv. Manufact. Tech. 62(5–8), 635–643 (2012). https://doi.org/10.1007/s00170-011-3815-3
3. Kulkarni, A. J., Durugkar, I. P., Kumar, M.: Cohort intelligence: a self-supervised learning behaviour. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1396–1400 (IEEE 2013, October). https://doi.org/10.1109/smc.2013.241
4. Momber, A.W., Kovacevic, R.: Principles of Abrasive Water Jet Machining. Springer, London (2012)
5. Patankar, N.S., Kulkarni, A.J.: Variations of cohort intelligence. Soft Computing 22(6), 1–17 (2017). https://doi.org/10.1007/s00500-017-2647-y
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