If we want to be a bit more precise, we know that when we change by t, t that's for linear approximation to how the function changes.

如果我们想更加精确一点，我们知道当t变化的时候，乘以导数就出现了，well, t, times, the, derivative, comes, in，这是函数变化量的线性近似。

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As one of the most important capability of ANN, function approximation ability can be used to design ANN model, which can characterize certain physics object.

函数逼近能力是ANN具有的重要性能之一，依据ANN具有的函数逼近能力，可用ANN模型去替代一个确定的物理对象。

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The numerical example shows that increasing the item of radial basis function is not a right way to improve the accuracy of results, and more approximation functions should be employed in the DRBEM.

计算结果表明增加径向基函数的项数并不是改善结果的好办法，应该将更多的函数引入双互易边界元法中。

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