湿地中，水位梯度是一个重要的环境梯度，湿地植物沿水位梯度式样反应的研究是湿地生态学重要的研究内容之一。
Water level gradient is an important environmental gradient in wetland, the research of reaction of wetland plant to water level gradient is an important content of wetland ecology.
在分析影响河道水位因素的基础上，采用基于梯度下降算法的BP神经网络模型推算河道水位，同时采用传统的上下游水位线性相关方法进行水位推算。
On the basis of the analysis of factors affecting the river water level, the BP neural network model, based on the gradient descending algorithm, is used to calculate the river water level.
与老式的冰层厚度传感器相比，新研制的冰层厚度-冰温传感器具有新的内部结构以及数据处理的算法，能够对冰层厚度、水位值、冰层内部的温度梯度进行准确测量。
Compared with the old-fashioned, the new sensor has a new internal structure and data processing algorithms, it can be able to measure ice thickness, water level values, the ice temperature gradient.
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