首页> 外文会议>Biennial IEEE Conference on Electromagnetic Field Computation;CEFC2010 >An adaptive optimization method using Kriging model and Latin hypercube design and its application to optimum design of PMLSM
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An adaptive optimization method using Kriging model and Latin hypercube design and its application to optimum design of PMLSM

机译:基于Kriging模型和拉丁超立方体设计的自适应优化方法及其在PMLSM优化设计中的应用。

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This paper presents a computationally efficient optimal design algorithm for electromagnetic devices by combining Kriging interpolation approximation of the objective function and genetic algorithm. In this method, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design (LHD). The proposed algorithm is applied to the optimum design of permanent magnet linear synchronous motor (PMLSM) and the computational efficiency is investigated.
机译:通过结合目标函数的克里格插值逼近和遗传算法,提出了一种计算效率高的电磁设备优化设计算法。在这种方法中,设计空间随着迭代而不断减少,并且使用拉丁超立方体设计(LHD)生成了帕累托最优采样点。将该算法应用于永磁直线同步电动机(PMLSM)的优化设计,研究了计算效率。

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