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The research of classification based on improved RBF neural network

机译:基于改进RBF神经网络的分类研究

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The approximation accuracy of RBF network constructed by the incremental learning algorithm to the target was not high. For function approximation or other requirements of high accuracy, such accuracy of RBF network model can not meet the requirements. We have improved this network model focused on three aspects to improve the bottleneck, and have an experiment and comparatively analyze these improvements algorithm on an UCI database, the experimental results show that the improved algorithm has better performances.
机译:由增量学习算法到目标的RBF网络的近似精度不高。对于高精度的功能近似或其他要求,RBF网络模型的这种准确性无法满足要求。我们改进了这个网络模型,专注于三个方面来改善瓶颈,并具有实验并相对分析这些改进算法在UCI数据库上,实验结果表明,改进的算法具有更好的性能。

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