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On Back-Propagation Network to Early Judgment of Seismic Sequences

机译:回到繁殖网络对地震序列的早期判断

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The early predictions of earthquake sequence types are studied using BP Network. Back-Propagation network is a feedforward neural network practiced by back propagation algorithm, is one of neural network modes applied widely. It not only can approximate any continuous function, has the strong nonlinear mapping ability, but also has a strong robustness, memory capacity and self-learning ability. On the basis of Ms ≥ 5.0 earthquake sequence materials in our country since 1970, It is effective for early predictions of earthquake sequence types that we divides the data in 5 time scales according to 1-7 days after the earthquake.
机译:使用BP网络研究了地震序列类型的早期预测。背部传播网络是反向传播算法实践的前馈神经网络,是广泛应用的神经网络模式之一。它不仅可以近似任何连续功能,具有强大的非线性映射能力,而且具有强大的鲁棒性,内存容量和自学能力。自1970年以来,在我国的MS≥5.0地震序列材料的基础上,对地震序列类型的早期预测有效,我们在地震后1-7天根据5次尺度将数据划分为5次。

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