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子神经网络
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  sub neural network
     The parameters of lubricating oil quality,vibration analyse,performance and the expert knowledge is used to construct the sub neural network respectively. With the evidence theory,the output of each neural network is fused,and the decision-making result received. It is showed that this method has a clear logic,and the assessment result accord with practicality.
     提出了一个柴油机状态评估模型,运用油液分析、振动分析和热力性能参数并根据专家知识分别构建子神经网络对柴油机进行状态评估,各部分的评估结果运用D-S证据理论进行融合判断,得到的融合决策评估结果表明,该方法逻辑清晰,评估结果符合实际。
短句来源
  sub-neural networks
     The signals are extracted and preprocessed in the signal pro-cessing subsystem. The diagnostic subsystem is the core,in which different signals are loaded into different sub-neural networks and diagnosed,then the results are sent into decision-making neural network for data fusion and last diagnosis decision.
     信号子系统负责信号的提取和预处理,诊断子系统则是诊断的核心,不同信号送入不同子神经网络进行诊断,结果通过决策神经网络进行数据融合,做出最后的诊断。
短句来源
     The integrated neural networks void under rigid pavement plate identification technology was put forward based on the information fusion theory. Taking the sub-neural networks as primary separation identification from different sides, the conclusions were gained through decision-making fusion.
     提出采用基于信息融合理论的集成神经网络技术对混凝土路面脱空状况进行识别,通过路面脱空输入特征向量的组合,用各子神经网络对混凝土路面脱空进行初步缺陷识别,然后对识别结果进行决策融合.
短句来源
  “子神经网络”译为未确定词的双语例句
     This problem can be solved through using several small and simple neural networks instead of a big and complex neural network, which will be a new research direction of this thesis in future.
     为了解决该问题,我们可以考虑采用子神经网络的思想,即把一个大的、复杂的神经网络的功能用几个简单的小神经网络来实现,这将是我们日后工作的一个研究方向。
短句来源
     The sub models can simulate the inference process of diagnosis system, and tune the weights, the membership functions of the feature data and the reliabilities of the rules.
     其中,子神经网络模型能够模拟诊断推理过程,动态地进行特征数据的权重、模糊等级的界限值和规则可信度的调整。
短句来源
     Because the object is a dynamic system, so we discussed the dynamic characteristics of artificial neural network used in identifying industrial process specially. With the background of power generating process, considering the characteristic of different bear, the paper proposed a novel method to identify the model that used sub network to identify the mathematics model of generating process in different loads. Considering the stability of the system, this paper introduced a new method to train neural network models with error feedback.
     本文主要研究人工神经网络在辨识实际工业系统中的应用.由于辨识的对象是一个动态系统,所以着重对人工神经网络在辨识工业生产过程的动态特性作了分析.本文以发电生产过程为背景,针对不同负荷下发电生产工况的特点,提出了用子神经网络分别辨识不同负荷下的发电生产过程.在考虑系统稳定的前提下,本文提出引入误差反馈来训练人工神经网络辨识模型的方法
短句来源
     After analysis of the current techniques of computerized monitoring and control systems of hydropower plants in China, a new computerized monitoring and control system based on elegant incorporation of expert system with neural network is put forward. Furthermore, multi neural network and data fusion techniques are also introduced into the system.
     在分析国内水电厂状态监测技术现状后 ,提出了一种基于神经网络和专家系统相结合的状态监测系统 ,并引入了子神经网络和数据融合技术。
短句来源
     This paper proposes an integrated handwritten recognition system based on multiple PSO neural networks.
     提出一种用于手写体字符识别的三级神经网络模型,各子神经网络均用粒子群优化算法(PSO)训练。
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  相似匹配句对
     Neural Net
     神经网络
短句来源
     Wavelet basis neural network and its modeling
     波基神经网络及其建模
短句来源
     IDENTIFICATION OF NEURAL NETWORK PREDICTOR BY MEANS OF PREDICTION COMPLEXITY
     基于预测复杂性的神经网络预测辨识
短句来源
     Neural Networks for Logic Circuits
     逻辑电路的神经网络
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     EXPLANATION OF"JIAO ZI
     “交”释义
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Predictive controller of memory recurrent neural network with adaptive learning rate which is used tO integratively control the water hammer and the frequency is presented.The controller consists of two networks which are used to predict and control respectively.The Predictive network provides the control sensitivity signal to the control network. A method of adaptive learning rate of memory recurrent neural network is presented according to the proved conditions of convergence and stability of learning and...

Predictive controller of memory recurrent neural network with adaptive learning rate which is used tO integratively control the water hammer and the frequency is presented.The controller consists of two networks which are used to predict and control respectively.The Predictive network provides the control sensitivity signal to the control network. A method of adaptive learning rate of memory recurrent neural network is presented according to the proved conditions of convergence and stability of learning and control Of memory recurrent neural networks. Simulation results show hat the controller can control an online real time nonlinear,the varying, multivariable hydrogenerator unit and integratively control the Water hammer and the frequency effectively.

提出一种自适应学习率记忆递归神经网络预测控制器及自适应学习率方法,它由用于预测和控制的子神经网络组成,预测子网络向控制子网络提供控制灵敏度信号;并证明了记忆递归神经网络学习的收敛性和稳定性条件.仿真结果表明控制器在线实时控制具有非线性、时变、多变量特性的水轮发电机组,对各种工况具有良好的性能.

A multi ANN adaptive controller for turbogenerators, addressed in this paper, is composed of two sub ANNs for predicting and control respectively. In the study it gives an on line realtime self learning and self adjusted algorithm based on errors back propagation. As a result of a simulation, it shows that this controller has a good performance for turbogenerators with nonlinear, time varying and multivariable characteristics.

一种水轮发电机组分层神经网络自适应预测控制器,采用多层前向神经网络,由两个分别用于预测和控制的子神经网络组成.提出一种误差反向传播在线实时自变学习率算法.仿真结果表明,该控制器对具有非线性、时变、多变量特性的水轮发电机组,具有良好性能.

When the parameter learning expert system was researched by modular neuro fuzzy network model, the whole model was decomposed into a few sub models of neuro fuzzy network with similar structure according to different abnormal statuses. The sub models can simulate the inference process of diagnosis system, and tune the weights, the membership functions of the feature data and the reliabilities of the rules. The results of the experiments using the data collected from a blast furnace show that the proposed...

When the parameter learning expert system was researched by modular neuro fuzzy network model, the whole model was decomposed into a few sub models of neuro fuzzy network with similar structure according to different abnormal statuses. The sub models can simulate the inference process of diagnosis system, and tune the weights, the membership functions of the feature data and the reliabilities of the rules. The results of the experiments using the data collected from a blast furnace show that the proposed method is feasible.

用模块化模糊神经网络模型进行参数学习专家系统的研究是根据不同的炉况类型及其相关变量将整个参数学习模型分解为几个结构相似的子模糊神经网络模型。其中,子神经网络模型能够模拟诊断推理过程,动态地进行特征数据的权重、模糊等级的界限值和规则可信度的调整。采用该方法对现场采集的数据进行实验,结果表明该方法具有较好的学习效果。

 
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