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In this report, the feasibility of predicting mechanical properties using magnetic parameters measurements and artificial neural network (ANN) will be presented. The yield and ultimate tensile strength are predicted by means of two back-propagation neural networks on the basis of hysteresis loop parameter measurements and sample thickness. Inductive(More)
In this paper, a novel method for predicting mechanical properties of cold- rolled low carbon steel based on magnetic parameter measurement using Adaptive Neuro Fuzzy Inference System (ANFIS) is presented. The Yield Stress (YS) and Ultimate Tensile Strength (UTS) are predicted using two ANFIS models on the basis of B-H curve parameter measurement. B-H curve(More)
In the present survey, the effects of skin-pass elongation and cold-rolling reduction on the formability parameters are studied. For this reason, three sets of samples, including those from industry and laboratory, were evaluated. In the first set, samples with different hot-rolling conditions were submitted to the same amount of skin reduction and their(More)
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