A novel hybrid method is proposed for neural network training. The method consists of two phases: in the first phase the bounds for the neural network parameters are estimated using a genetic algorithm that uses intervals as chromosomes. In the second phase a genetic algorithm is used to train the neural network inside the bounding box located by the first phase. The proposed method is tested on a series of well-known datasets from the relevant literature and the results are reported.

中文翻译：

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找到具有间隔的神经网络的边界框

提出了一种新的混合方法用于神经网络训练。该方法包括两个阶段：在第一阶段，使用遗传算法（使用区间作为染色体）估计神经网络参数的范围。在第二阶段，使用遗传算法来训练位于第一阶段所定位的边界框内的神经网络。在相关文献的一系列知名数据集上对提出的方法进行了测试，并报告了结果。