neural network model的例句大全

Research on Target Identification Method Based on Rough Set-Neural Network Model

基于粗集-神经网络模型的目标识别方法研究

BP artificial neural network model of groundwater dynamic and analysis on the improved grey slope coefficient correlation degree

地下水动态的BP神经网络模型及改进的灰色斜率关联度分析

RBF and BP neural network modeling are introduced and used to establish the compensation models corresponding the temperature measuring point optimization schemes. The final compensation model is determined after the analysis comparison.

研究RBF及BP神经网络建模理论，针对不同的测温点优化方案，建立对应的主轴热误差补偿模型，经过分析比较，确定了最终的补偿模型。

Results: The goodness of fit of the neural network model in training set was 97.3%, and the classification accuracy in testing set was 95.4%.

结果：RBF网络对训练集的拟合度为97.3%，对测试集的分类准确率为95.4%。

An Artificial Neural Network Model for Prediction of Thickness Ratio of the Rolled Al/ Cu Sheet

黄铜/铝双金属轧后厚比预测的神经网络模型

Based on the Back-Propagation neural network model, a three-layer network system is established to process fabric handle signals.

基于反向传播神经网络模型（BP）建立了3层网络系统用于处理织物风格信号。

A method combining temporal difference method with neural network model is applied to predict the sulfur content of the hot metal.

将时差方法与人工神经元网络方法有机地结合起来，提出了一种在高炉铁水含硫量预报中的应用策略。

Based on the MWD estimated by the neural network model and optimal performance index, the control sequences are synthesized in order to make MWD close to the target distribution.

根据预估的分子量分布数据和事先确定的性能指标，使用最优化方法，计算出控制序列，使过程输出达到给定的理想分布。

Applied neural network technology on prediction of construction tender price index. Put forward two sensitivity analysis methods for variables in neural network model and applied on the indicators related to tender price index.

将神经网络技术应用于建筑投标价格指数预测，提出了两种神经网络的变量敏感性分析方法，并用提出的方法分析了投标价格指数所涉及变量的敏感性。

A Neural Network Model Design with OOP and Its Application in Nonlinear Dynamic System Identification

面向对象的神经网络程序设计及其在非线性动态系统辨识中的应用

A neural network model for estimating sea surface chlorophyll from thematic mapper imagery

用TM图象估算海表面叶绿素浓度的神经网络模型

In order to improve the recognition performance of synergetic neural network further, a hierachical synergetic neural network model for multifont character recognition was proposed.

提出了一种用于多字体字符识别的分级协同神经网络模型。

Using the data obtained from a test vehicle, a neural network model of automotive for velocity tracking is developed at first.

利用试验汽车所获得的数据，首先开发出用于车速控制的神经网络模型。

Based on the neural network model of limit load of rock socketed segment of pile, the analysis method of characteristic parameters is proposed by means of self organizing character map network. The analysis results are consistent with practical results.

以嵌岩桩嵌岩段承载力极限值估计的BP网络模型为基础，提出了用自组织特征映射网络来分析问题的特征参数的方法，其分析结果与工程实践结果相一致；

Learning Strategies for Test Generation Based on Neural Network Model

基于神经网络模型测试生成的学习策略

Compared to the dynamic systems with fixed time delay, the neural network model with time-varying delay is better to simulation of control system.

相比于时滞是定值的动力学系统，含有时变时滞的神经网络模型则是对控制系统更好的模拟。

On the basis of constructing the time series data with the same time interval by interpolation method, and treating the data with normalization method, a time series RBF neural network model about soft-base sedimentation is established. The sedimentation is predicted by training the network model.

采用插值方法构建时间间隔统一的时间序列数据并进行归一化处理，在此基础上建立了沉降变形时间序列的RBF神经网络模型，通过训练网络模型来预测沉降量。

Combining the traffic investigative data, the neural network was trained using the technique of simulation and optimization. It is found that the neural network model can describe the real behavior of traffic flow more accurately.

结合交通调查数据，利用仿真和优化技术对神经网络进行训练，从而获得了比较准确的描述交通流真实行为的模型。

Classify time quota standard tables according to inductive method, and for every type of standard to create a neural network model to simulate it.

在此基础上采用归纳法，将工时定额标准表按相似性进行分类后，针对每一类标准表创建一种神经网络模型来模拟。

The application in AMT test vehicle shows that the dynamic shift schedule with 3-parameter based on neural network model of engine is superior to the shift schedule with 2-parameter in dynamic performance and fuel economy.

该方法在AMT样车开发中的应用表明：与两参数换挡规律相比，基于神经网络发动机模型的动态三参数换挡规律可使自动变速汽车具有更好的动力性和燃油经济性。