边坡稳定分析的三维Spencer法

将边坡稳定分析中的二维Spencer法拓展到了三维。该方法对所有条块满足力的平衡以及整体力矩平衡，克服了其他方法中只适用对称问题的缺点，不需已知滑动方向，还可根据滑面的几何特征，进一步得到各条块局部的稳定性系数及其潜在的滑动方向。此外，给出了该方法的实现步骤，其算法的收敛性也较好。最后以不对称问题为算例，并与其他文献中的结果进行比较，验证了该方法的可行性和有效性。

A novel FOCAL technique based on BP-ANN

In this paper, the feed-forward back-propagation artificial neural network (BP-ANN) algorithm is introduced in the traditional Focus Calibration using Alignment procedure (FOCAL) technique, and a novel FOCAL technique based on BP-ANN is proposed. The effects of the parameters, such as the number of neurons on the hidden-layer and the number of training epochs, on the measurement accuracy are analyzed in detail. It is proved that the novel FOCAL technique based on BP-ANN is more reliable and it is a better choice for measurement of the image quality parameters. (c) 2005 Elsevier GmbH. All rights reserved.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

基于SHAW模型的黄土高原半干旱区农田土壤水分动态模拟

黄土高原半干旱区土壤蒸发强烈,准确地掌握土壤水分动态对于旱地农业水分管理至关重要。应用基于物理基础的一维水热耦合SHAW(The Simultaneous Heat and Water)模型,模拟了陕西子洲岔巴沟流域1964~1967年土壤水分和土壤蒸发的动态特征,以及神木六道沟流域2006年坡地和梯田土壤水分变化。结果表明,除表层土壤水分模拟结果偏差较大,其他土层模拟值与实测值基本吻合,模拟期土壤水分模拟的相对平均绝对误差(Relatively Mean Absolutely Error,RMAE)为5.2%~11.4%。1964~1967年土壤累积蒸发量模拟值与实测值平均相对偏差为0.8%~6.1%,土壤蒸发的模拟值与实测值较为一致。因此,SHAW模型可以用于黄土高原半干旱区农田土壤水分动态规律研究。