方法：应用人工神经网络误差反向传播模型进行含量测定。
Method:Artificial neural network based on error back propagation was used.
本文根据人工神经网络的一典型模型—反向传播模型，以及地震荷载下的各项土的物理—力学参数，建立了土液化类型的神经网络数学模型。
A typical artificial neural network model-back-propagation model was presented for prediction on the soil liquefaction type based on the physical parameters of soils under earthquake.
利用误差反向传播的改进算法对样本数据进行训练，并用另外的一些样本数据验证模型的应用效果。
Using the improved error backward propagation, the model is trained with stylebook data and validated its effect by other stylebook data.
模型分别采用多元逐步回归方法和反向传播方法。
The model used multiple stepwise regression method and back propagation method independently.
针对化工中经常遇到的高度非线性问题，以塔板研究中的泄漏模型为例，采用人工神经网络中的BP(反向传播)算法进行处理。
High nonlinear problem which is often met in Chemical engineering, taking the study of tray leakage mode as example, is treated by adopted BP (back propagation) algorithm in artificial neural network.
该文介绍了一种基于人工神经网络的软件失效预测模型，给出了基于反向传播算法的多层前向网络的网络结构。
This paper presents a kind of software faults prediction model based on artificial neural network and the structure of the feed-forward multi-layer network with backpropagation learning algorithm.
为了对环境质量进行综合评价，运用误差反向传播算法的人工神经网络方法建立了环境质量评价的B -P决策模型。
In order to evaluate environmental quality, this paper proposed the B-P decision model for environmental quality by using artificial neural network method.
基于反向传播（BP）神经网络，建立了民用航空航段安全风险评估模型。
This research built a flight phase safety risk assessment model basing on Back Propagation(BP) neural network.
利用神经网络的误差反向传播算法(BP算法)，结合告警、天气和工程设计几方面的数据资料建立了微波中继段告警分析预测模型。
By means of BP (error back propagation) artificial nerve network, with data from alarm, weather and engineering documents, microwave hop performance analysis and forecast model is established.
本文将神经网络引入到航材需求分析领域中，应用误差反向传播网络建立模型进行预测，并对模型结果进行了分析。
This paper introduces Neural net to the fields of air-materials demands analysis, and applies Back Propagation network to forecast.
在实际工业数据上进行的实验结果表明，支持向量机模型对丙酮纯度具有良好的预测效果，性能优于反向传播神经网络和径向基网络模型。
The experimental results on the real industrial data demonstrate that the model based on SVM achieves good performance and has less prediction errors than those of BPNN and RBFNN models.
第二种模型是神经网络反向传播算法模型。
本文分析了一种动态补偿神经网络模型，模型的训练利用反向传播原理实现。
A neural network model with dynamical compensating capability is analyzed. During the training of this network model, we apply the principle of dynamic error back-propagation.
应用神经网络的误差反向传播算法(BP)和大量的实测数据样本训练出了能在线诊断四种加工状态的BP模型并成功地诊断了实际加工状态。
The BP algorithm of Artificial Neural Networks and lots of experimental samples were used in training the BP model which succeeded in diagnosing four kinds of operational status.
使用自适应谐振理论（ART）和误差反向传播（B）两种神经网络，开发了汽轮发电机组振动故障诊断模型。
The vibrating fault diagnosis system for turbo-generator unit based on ART and BP network is developed in this work.
使用自适应谐振理论（ART）和误差反向传播（B）两种神经网络，开发了汽轮发电机组振动故障诊断模型。
The vibrating fault diagnosis system for turbo-generator unit based on ART and BP network is developed in this work.
应用推荐