2020
DOI: 10.33640/2405-609x.1508
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A Support Vector Machine-based Prediction Model for Electrochemical Machining Process

Abstract: Manufacturing of quality products is one of the core measures to address competitiveness in industries. Hence, it is always necessary to accomplish quality prediction at early stages of a manufacturing process to attain high quality products at the minimum possible cost. To achieve this goal, the past researchers have developed and investigated the applications of different intelligent techniques for their effective deployment at various stages of manufacturing processes. In this paper, support vector machine … Show more

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“…The SVR is a supervised learning technique, applied both for classification and regression, and is based on the principle of support vector machine (SVM), which develops a hyperplane between two sets of data [22,23]. A margin is created while developing two parallel hyperplanes, each on the opposite side, and its width reaches to the maximum at optimal solution.…”
Section: Support Vector Regressionmentioning
confidence: 99%
“…The SVR is a supervised learning technique, applied both for classification and regression, and is based on the principle of support vector machine (SVM), which develops a hyperplane between two sets of data [22,23]. A margin is created while developing two parallel hyperplanes, each on the opposite side, and its width reaches to the maximum at optimal solution.…”
Section: Support Vector Regressionmentioning
confidence: 99%