The computing result, added into error is used as the solving condition of the inverse problem.
用正问题的计算结果加上误差作为反问题的求解条件。
This thesis focuses on determination of parameters in a two-dimension heat conduction equation on the MPI network parallel environment, by solving an inverse problem using the regularization method.
本文是在MPI网络并行环境中，将求解二维热物性方程参数的反问题用正则化方法结合并行遗传算法进行数值求解。
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.
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。
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