提出一种新的神经网络模型—时滞标准神经网络模型(DSNNM)，它由线性动力学系统和有界静态时滞非线性算子连接而成。

A novel neural network model, named delayed standard neural network model (DSNNM), is proposed, which is the interconnection of a linear dynamic system and a bounded static delayed nonlinear operator.

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本文根据我国垃圾堆放场的具体情况，提出稳定化程度的判别评价指标体系，并且确定稳定化程度的判别标准，运用BP神经网络建立垃圾堆放场稳定化程度的综合判别模型。

This paper sets up index system and its standard of judgment for refuse stabilization degree according to these dumps in our country and builds integrated judgment model based on BP neural network.

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通过与标准BP算法的比较，表明这两种改进方法都能有效地提高神经网络模型的精度。

By comparing with standard BP model, it shows that both the two improved methods can improve the precision of ANN efficiently.

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