Abstract
In this paper, the estimations of mechanical property of rolled steel bar by using quantum neural network (QNN) were proposed. Based on the learning capability of neural network, the nonlinear, complex relationships among the steel bar, the billet materials and the control parameters of production could be automatically developed. Such an artificial intelligent (AI) estimator then can help the operation technician to set the related control parameters of rolling process. Not only the quality of steel bars could be improved, but also the cost of bar’s production could be greatly reduced.
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Yang, JP., Chen, YJ., Huang, HC., Tsai, SN., Hwang, RC. (2009). The Estimations of Mechanical Property of Rolled Steel Bar by Using Quantum Neural Network. In: Wang, H., Shen, Y., Huang, T., Zeng, Z. (eds) The Sixth International Symposium on Neural Networks (ISNN 2009). Advances in Intelligent and Soft Computing, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01216-7_85
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DOI: https://doi.org/10.1007/978-3-642-01216-7_85
Publisher Name: Springer, Berlin, Heidelberg
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