比较分析了最小二乘支持向量机（LSSVM）和广义回归神经网络（GRNN）这两种方法的特点。

The features of two methods, i. e. least square support vector machine (LSSVM) and generalized regression neural network (GRNN) are compared and analyzed.

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广义回归神经网络在逼近能力、分类能力和学习速度方面具有较强优势。

General regression neural network is proved with certain superiority in the ability of approaching, classification and learning speed.

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介绍了径向基函数网络的函数逼近原理和方法，提出了一种基于广义回归神经网络（GRNN）的传感器非线性误差校正方法。

The RBF network function approximation theory and method are introduced, and the method of nonlinear error correction of sensor is presented based on generalized regression neural network(GRNN).

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广义回归神经网络（GRNN）和遗传算法（GA）都是在模拟人的生理活动进而提出的人工智能技术。

The generalized regression neural network(GRNN) and the genetic algorithm(GA) are regarded as the artificial intelligence techniques.

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本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类。

This case USES combined with fuzzy clustering and generalized regression neural network clustering algorithm for intrusion data classification.

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本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类。

This case USES combined with fuzzy clustering and generalized regression neural network clustering algorithm for intrusion data classification.

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