A self_calibrating PCC CAM controller based on RBF (Radial Basis Function) network is presented.

提出了一种基于径向基函数(RBF)网络的具有自校正功能的PCC协联控制器。

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Using RBF (Radial Basis Function) network as the soft-sensing model, its natural to introduce regularization learning algorithm.

以径向基函数神经网络作为软测量模型，在软测量建模中引入正则化学习算法。

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For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.

针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。

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Based on the idea of data parallelism, a parallel training model for RBF (radial basis function) neural network in time-series prediction to improve the training speed is proposed.

根据数据并行的思想，提出了在时序预测中并行训练神经网络的模型，以提高训练速度。

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Based on the idea of data parallelism, a parallel training model for RBF (radial basis function) neural network in time-series prediction to improve the training speed is proposed.

根据数据并行的思想，提出了在时序预测中并行训练神经网络的模型，以提高训练速度。

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