三次样条插值逼近函数 cubic spline interpolation function approximati
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在策略迭代结强化学习方法的值函数逼近过程中，基函数的合理选择直接影响方法的性能。
An appropriate selection of basis function directly in? Uences the learning performance of a policy iteration method during the value function approximation.
应用LOO估算选择的核函数模型能够较好地逼近最佳值。
The kernel function model selected by LOO estimation can approach the best value satisfactorily.
只要选用相应的目标函数，曲面插值、逼近、拼接和光顺都可以使用优化技术统一处理。
Optimization techniques are being applied to solve the problems of surface interpolation, approximation, smooth joining and fairing, aiming at corresponding goal functions.
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