1.
Inflammable gas analysis based on distributed multi-subnet neural networks
基于分布式多子网神经网络的可燃气体分析
2.
Research on Neural Networks and Distributed Computing Based on Multidimensional Data Analysis;
基于多维数据分析的神经网络与分布式计算研究
3.
Grey box model of polymer molecular weight distribution using hybrid discrete orthogonal polynomial neural network
利用离散正交多项式组合神经网络建立聚合物分子量分布灰箱模型
4.
STUDY ON NEURAL NETWORK FOR THE RECOGNITION OF BLASTFURNACE TOP TEMPERATURE DISTRIBUTION
高炉炉顶温度分布模式识别神经元网络的研究
5.
Research on the Application of the Distributed Intrusion Detection System Based on the Neural Network Technology
基于神经网络技术的分布式入侵检测系统研究
6.
Distributed rainfall interpolation using BPANN
基于BP人工神经网络的分布式降雨量插值估算
7.
Global attractor of a class of recurrent neural network with S-type distributed delays
一类S-分布时滞递归神经网络的全局吸引子
8.
Development of a Distributed Protection Principle Based on RBF Neural Network in Distribution System with High Penetration of DG
高DG渗透配网基于RBF神经网络的分布式保护原理
9.
Research on Parametric Multiwavelets and Multiwavelets Neural Networks;
参数化多子波及多子波神经网络研究
10.
The result showed that layered multi-subnet neural network was suitable to online eddy current testing.
结果表明，层次式多子网神经网络适用于实时在线检测。
11.
Modeling and Controling Molecular Weight Distribution for Polymerization Processes Via Neural Networks;
利用神经网络实现聚合反应分子量分布的建模与控制
12.
Study on Neural Network for the Recognition of Blast Furnace Top Gas Temperature Distribution;
高炉炉顶煤气温度分布模式识别神经元网络的研究
13.
The Study on Distributed Precipitation Estimation Model & Method Based on MODIS & Artificial Neural Networks;
基于MODIS和人工神经网络的流域分布式降雨量估算模型和方法研究
14.
The Research of Distributed Ids Based on Improved BP Neural Network;
基于改进BP神经网络的分布式入侵检测模型研究
15.
Synchronous Closing Time Precalculation Based on Distributed Neural Network
基于分布式神经网络的同步合闸时间预测方法研究
16.
INTELLIGENT-AGENT DISTRIBUTED INTRUSION DETECTION SYSTEM BASED ON IMPROVED BP NEURAL NETWORK
基于改进BP神经网络的智能Agent分布式入侵检测系统
17.
Because neural networks have a very strong ability in pattern recognition, an NN classifier is used in the multi-parameter recognition of fault signals.
充分利用了神经网络极强的模式分类能力，用神经网分类器对故障信号进行多参量识别。
18.
Global Periodic Attractor of Infinite Internal Static Neural Networks with S-type Distributed Time Delays
无穷区间上S分布时滞静态递归神经网络模型的全局周期吸引子