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Effective strategies of metamodelling of industrial metallurgical processes

机译:工业冶金过程的元建模有效策略

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The main objective of the metamodelling is replacing the model of analysed process by its simple (with respect to the computation time) approximation. Metamodel gives a significant reduction of computation time of considered process simulation, as well as its further analysis (sensitivity analysis, optimization, etc.). The paper discusses the idea of metamodelling and compares the effectiveness of three techniques: Response Surface Methodology (RSM), Kriging method and Artificial Neural Network (ANN) applied to the benchmark functions. An example of the use of the considered metamodelling techniques in optimization of the problem of laminar cooling of rolled Dual Phase (DP) steel strips is presented. Metamodelling and optimization of a real industrial metal forming problems seems a novel approach in the field of research on Artificial Intelligence and Optimization practical applications.
机译:元建模的主要目的是通过其简单的(相对于计算时间)近似替代分析过程的模型。元模型极大地减少了所考虑的过程仿真及其进一步分析(灵敏度分析,优化等)的计算时间。本文讨论了元建模的思想,并比较了三种技术的有效性:响应面方法论(RSM),克里格方法和人工神经网络(ANN)应用于基准功能。给出了在优化轧制双相(DP)钢层流冷却问题中使用已考虑的元建模技术的示例。真正的工业金属成型问题的元建模和优化似乎是人工智能和优化实际应用研究领域中的一种新方法。

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