Kohonen自适应神经网络,Kohonen self-adaptive neural network
1)Kohonen self-adaptive neural networkKohonen自适应神经网络
2)kohonen neural networkKohonen神经网络
1.Triangle mesh surface reconstruction based on Kohonen neural network and fuzzy clustering technique;基于模糊聚类的Kohonen神经网络三角网格曲面重建
2.Application of Kohonen Neural Network Model to Classifying Swelling Potential Grades of the Expansive Soil;Kohonen神经网络模型在膨胀土膨胀潜势分类中的应用
3.B-spline surface reconstruction based on Kohonen neural network;基于Kohonen神经网络的B样条曲面重构
英文短句/例句
1.Land Use Zoning in China Based on Kohonen Network;基于Kohonen神经网络的中国土地资源综合分区
2.Application of Kohonen Neural Network on Sports Cluster Analysis;Kohonen神经网络在体育运动聚类分析中的应用
3.Dynamic Scheduling of Photolithography Process Based on Kohonen Neural Network基于Kohonen神经网络的晶圆光刻流程动态调度方法
4.A Web User Access Pattern Mining Algorithm Based on the Dual Kohonen Neural Network基于双Kohonen神经网络的Web用户访问模式挖掘算法
5.A Way of Kohonen Neural Network Based Model for User Behavior Pattern Mining一种基于Kohonen神经网络Web用户行为模式的挖掘方法
6.A Kohonen Neural Network Based Model for User Access Pattern Mining;基于kohonen神经网络的用户访问模式挖掘模型的研究
7.Military Intelligence Quality Evaluation Based on Kohonen Network;基于Kohonen网络的军事情报质量评估方法
8.Improved Clustering Algorithm Based on Fuzzy Kohonen Clustering Network基于模糊kohonen聚类网络的改进算法
9.Research on Classification of Domestic Tourism Demand among Urban Residents Based on Kohonen Network;基于Kohonen网络的城市居民国内旅游需求分类研究
10.Kohonen Network Discrimination of Wood Materials Based on NIR Spectroscopy基于近红外光谱法的木材原料的Kohonen网络分类法
11.BP Network and Neual Network Tool Kit in MATLABBP神经网络与MATLAB神经网络工具箱
12.Classification of Highway Transportation Hubs Combined Factors Analysis with Kohonen Network基于因子分析与Kohonen网络的公路运输枢纽分类方法
13.Hopfield neural network霍普菲尔德神经网络
14.The Stability of Hopfield Neural Networks;Hopfield型神经网络稳定性
15.Research Headway of Hopfield Neural Networks;Hopfield神经网络研究进展
16.Multiple neural network ensembles method based on learning knowledge database基于神经网络知识库的多神经网络集成方法
17.Development and Prospect of Artificial Neural Network and Neural Network Control(NNC)人工神经网络与神经网络控制的发展及展望
18.Internet time-delay prediction based on RBF Neural NetworkRBF神经网络在网络时延预测中的应用
相关短句/例句
kohonen neural networkKohonen神经网络
1.Triangle mesh surface reconstruction based on Kohonen neural network and fuzzy clustering technique;基于模糊聚类的Kohonen神经网络三角网格曲面重建
2.Application of Kohonen Neural Network Model to Classifying Swelling Potential Grades of the Expansive Soil;Kohonen神经网络模型在膨胀土膨胀潜势分类中的应用
3.B-spline surface reconstruction based on Kohonen neural network;基于Kohonen神经网络的B样条曲面重构
3)Kohonen neural networksKohonen神经网络
1.Region classification of forest ecological economic system based onKohonen neural networks;基于Kohonen神经网络的森林生态经济区域分类
2.In comparison with theKohonen neural networks, the structure of the compete study networks is relatively simple because it does not consider neighboring neural units.竞争学习网络与Kohonen神经网络相比,由于不考虑邻域神经元,其网络结构相对简单。
4)self-adapting neural network自适应神经网络
1.The present article intends to introduce a new approach to solving the problem in determining the remnant methane quantity in fallen coals by means ofself-adapting neural network.基于此 ,作者提出自适应神经网络的落煤残存瓦斯量预测模型 ,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。
5)adaptive neural network自适应神经网络
1.Fuzzy tracking control for fighter based onadaptive neural network;基于自适应神经网络的歼击机模糊跟踪控制
2.Directadaptive neural network control for uncertain nonlinear system with disturbance;不确定非线性系统的直接自适应神经网络控制
3.Robust H_∞ control for a class of uncertain nonlinear systems based onadaptive neural networks;基于自适应神经网络的一类不确定非线性系统的鲁棒H_∞控制
6)self-adaptive neural network自适应神经网络
1.Theself-adaptive neural network algorithm about adjusting momentum vector and learning rate was discussed in this paper.探讨了动量系数和学习率自适应调整的神经网络算法,给出了动量系数和学习率的调整方法,并作为机械故障的特征识别方法,以小波分析技术作为机械故障特征信号的提取手段,由此建立了基于小波与自适应神经网络的旋转机械故障智能诊断系统,给出了诊断系统的训练学习方式和工作方式,通过实际测试数据酌诊断结果说明此诊断系统对故障诊断是有效的。
2.Theself-adaptive neural network about adjusting mom en tum vector and learning rate, and the selection of characteristic parameters of void identification on rigid pavement for nondestructive testing (NDT) fast and validly are discussed, and the frequency drawdown ratio as characteristic parame ters put forward in this paper.利用有限元方法对刚性路面脱空进行数值模拟 ,同时采用声振法研究了刚性路面板声学特征变化的关系 ,分别获取训练样本数据 ,通过自适应神经网络对刚性路面脱空进行了识别研究。
3.Theself-adaptive neural network algorithm about adjusting momentum vector and learning rate is discussed.以频谱分析作为机械故障特征信号的提取手段,由此建立了基于自适应神经网络的旋转机械故障智能诊断系统,给出了诊断系统的训练学习方式和工作方式,通过实际测试数据的诊断结果,说明此诊断系统对故障诊断是有效的。
延伸阅读
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