Surface roughness prediction method of titanium alloy milling based on CDH platform

نویسندگان

چکیده

Generally, off-line methods are used for surface roughness prediction of titanium alloy milling. However, studies show that these have poor accuracy. In order to resolve this shortcoming, a method based on Cloudera’s Distribution including Apache Hadoop (CDH) platform is proposed in the present study. regard, data analysis and process designed CDH, which can upload, calculate, store real time. Then combined with Harris hawk optimization (HHO) algorithm pattern search strategy, an improved (IHHO) accordingly. applied optimize support vector machine (SVM) predict CDH platform. The obtained results accuracy IHHO reaches 95%, higher than conventional SVM, BAT-SVM, gray wolf optimizer (GWO-SVM), whale (WOA-SVM).

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ژورنال

عنوان ژورنال: The International Journal of Advanced Manufacturing Technology

سال: 2022

ISSN: ['1433-3015', '0268-3768']

DOI: https://doi.org/10.1007/s00170-021-08554-6