说明：  广义回归神经网络 CGRNN, Generalized Regression Neural Network）是美国学者 Donaid F. Specht 在 1991 年提出的，它是径向基神经网络的一种。 GRNN 具有很强的非线性映射能力和柔性网络结构以及高度的容错性和鲁棒性，适用 于解决非线性问题。
(Generalized Regression Neural Network (CGRNN) was proposed by Donaid F. Specht, an American scholar, in 1991. It is a kind of radial basis function (RBF) neural network. GRNN has strong non-linear mapping ability, flexible network structure, high fault tolerance and robustness, and is suitable for solving non-linear problems.)