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1)  wavelet neural network with improved structure
改进结构的小波神经网络
2)  Variable-structure BP wavelet neural networks
变结构BP小波神经网络
3)  improved neural network
改进的神经网络
4)  Dyadic wavelet neural network
二进小波神经网络
5)  improved BP neural network
改进的BP神经网络
1.
As artificial neural network method not only possesses ability of self-taught, self-organized and high non-linear mapped, but also can consider both quantitative and quanlitative factors, based on improved BP neural network, a lot of neural network models are established to predict parameters of surfac.
利用大量的地表移动实际观测数据样本对该网络模型进行训练和学习,并用该网络模型对地表移动参数进行预计,结果表明,该改进的BP神经网络具有收敛速度快、预计参数精度高的优点,从而为开采沉陷地表移动预计中参数的选取提供了新方法。
2.
On the basis of the gray prediction models(the equidistant gray model,the non-equidistant gray model,the optimized gray model) and the improved BP neural network models(the gradient descending algorithm of having momentum and Levenberg-Marquardt algorithm),the mechanical characteristics of the concrete-lined shaft wall are predicted.
1作为预测预报软件开发工具,采用灰色预测模型(等距灰色模型、非等距灰色模型、优化灰色模型)及改进的BP神经网络预测模型(有动量的梯度下降法、Levenberg-Marquardt算法)对混凝土井壁结构的受力状态进行预测。
6)  improved fuzzy neural network
改进的模糊神经网络
1.
According to the interferential factors above,a new short-term load forecasting approach based on improved fuzzy neural network is presented by introducing "intervening item".
针对这些干扰因素,引入了"干预项",进而提出了一种改进的模糊神经网络预测的新方法;阐述了应用该方法进行短期负荷预测的基本原理、网络模型和预测过程。
2.
In this article,the improved fuzzy neural network with time-varying model in fitting and forecasting of the horizontal displacement monitoring of one dam is used,and the BP model is the comparative example.
针对时变监控模型比常规监控模型更有效且能准确进行变量分离,通过改进的模糊神经网络(IFNN)结合时变模型对陈村水库大坝的水平位移进行拟合与预测,并与BP模型做了比较。
补充资料:改进
改变旧有情况,使有所进步:~工作ㄧ操作方法有待~。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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