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1)  improved back-propagation network
改进的BP网络
2)  Improved BP network
改进BP网络
1.
Research on load forecasting of fusion between D-S evidential theory improved BP network;
D-S证据理论融合改进BP网络的短期负荷预测研究
2.
In view of the simplicity of its using and expressing knowledge and its ignoring expert knowledge,this paper proposes an improved BP network for fault diagnosis,which combines network with expert system and gains the advantages of the two.
针对BP网络利用知识和表达知识的方式单一,忽略专家知识的缺点,提出了一种结合专家知识的改进BP网络,并应用于故障诊断。
3)  Improved BP neural network
改进BP网络
1.
An identification method combining improved BP neural network and genetic algorithm is put forward in this paper.
本文提出了一种结合改进BP网络和遗传算法的辨识方法。
4)  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。
5)  Improved BP nerve network
改进的BP神经网络
1.
Improved BP nerve network, adopting the momentum method and study velocity from orientation, was applied to the fault diagnosis of the fan.
根据风机的故障诊断特点,确定神经网络的结构与参数,并制作了相应的故障诊断界面,最后通过风机的故障诊断实例表明:改进的BP神经网络提高了学习速度,有效地抑制了网络陷于局部极小,缩短了学习时间,是风机故障诊断的有效方法。
2.
As for the deficiency of BP network, this paper suggests an improved BP nerve network model which can serve in breakdown diagnose of tubine generator set.
就BP网络的不足,提出了一种改进的BP神经网络模型,用于汽轮发电机组故障的诊断。
6)  improved BP-NN model
改进的BP神经网络模型
1.
This paper puts forward the improved BP-NN model and sums up the most affecting settlement factor of highway soft foundation.
通过对模型的建立、训练和验证,以及与其他方法的对比表明,改进的BP神经网络模型在非线性建模方面具有泛化性强、计算精度高、操作简便的独特优势,具有广阔的工程应用前景。
补充资料:神经网络BP算法
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性质:它是D.Rumellart等人提出的一个监督训练多声能神经网络的算法,每一个训练范例在网络中经过两遍传递计算:一遍向前传播计算,从输入层开始,传递各层并经过处理后,产生一个输出,并得到一个该实际输出和所所需输出之差的差错矢量;一遍向反向传播计算,从输出层至输入层,利用差错矢量对权值进行逐层修改。BP算法有很强的数学基础,戏剧性地扩展了神经网络的使用范围,产生了许多应用成功的实例,对神经网络研究的再次兴起过很大作用。

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