本文讨论了电磁场逆问题的求解方法，系统地进行了随机类优化算法的改进研究以及轮毂式永磁电机优化设计的应用研究。
This paper mainly presents the method of solving inverse electromagnetic problems, the improvement of the stochastic optimization algorithm and the optimal designing of outer-rotor permanent motor.
因而具有“上山”性的随机类优化算法成为求解逆问题的主要数学工具。
Due to its character of "uphill climbing", stochastic optimization algorithm is widely used to solve inverse problems.
针对科学和工程研究中的病态逆问题，提出了基于多目标优化的求解方法。
The resolution strategy for ill-posed inverse problems encountered in science and engineering researches is put forward, based on multi-objective optimization.
研究了特征值反问题求解的几种神经网络模型：直接逆模型，间接逆模型，优化方法模型，指出了各种方法的应用范围。
In this paper, several artificial neural network based models of solving inverse eigenvalue problem and their characters are studied. These models are direct, indirect and optimization inverse models.
因此，本文为电磁场逆问题的求解计算提供他一种可供选择的全局优化算法。
Thus an alternative for the global optimization of inverse problems in electromagnetics is introduced.
该算法中，径向基函数神经网络(RBFNN)用作前向模型，IGLSA用于求解逆问题中的优化问题。
In the algorithm, the radial-basis function neural network (RBFNN) is utilized as forward model, and the IGLSA is used to solve the optimization problem in the inverse problem.
提出一种电容射频热疗中优化求解预期深部有效热区分布逆问题的方法。
An inverse optimization method, applied in hyperthermia to search the ideal heating physical configurations in the expected temperature distribution of heat-field, was proposed.
提出一种电容射频热疗中优化求解预期深部有效热区分布逆问题的方法。
An inverse optimization method, applied in hyperthermia to search the ideal heating physical configurations in the expected temperature distribution of heat-field, was proposed.
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