Add the following property to $HADOOP_HOME/conf/core-site.xml to set the NN IP/ port
把以下属性添加到 $HADOOP_HOME/conf/core-site.xml 中以设置NNIP/端口
This article assumes you choose host001 as NN, host002 as JT, and host003 as SNN.
本文假设选择host001作为NN，host002 作为JT，host003 作为SNN。
To get Psyco to do the desired optimization, you need to either add psyco.bind(NN) to code_recognizer.py or add psyco.jit() to bpnn.py.
要使Psyco 进行期望的优化，需要将psyco.bind(NN)添加到 code_recognizer.py或者将psyco.jit() 添加到bpnn.py 。
It is used to optimize the structure and delete the redundant connections in training the weight value of nn.
该算法在训练神经网络的权值的同时，优化其连接结构，删除冗余连接。
Combined with nn, this method can solve nonlinear coupled problems, which cannot be solved by normal distributed control.
结合神经网络可以解决常规分布式控制难于解决的非线型耦合问题。
Compared with the classical method, the identification accuracy and the generalization capability of nn are testified to be superior in either the free - noise or noisy case.
结果表明，在无噪和有噪情况下，神经网络模型的辨识精度和泛化能力都要优于传统方法。
One advantage of the algorithm is that the hidden-mapping model of NN makes it difficult to get the direct mapping function of the ordinary chaos encryption algorithm.
该算法的优点之一是神经网络（NN）隐式混沌映射关系使直接获取映射关系变得困难。
Experiment result indicates it is entirely feasible to exercise NN technology processing real - time diagnose in electronic - control diesel trouble diagnose system.
实验结果表明，在电控柴油机故障诊断系统中运用神经网络技术进行实时诊断是完全可行的。
A partial features based similarity K-NN retrieval method is proposed.
提出了基于部分特征的K -近邻相似检索方法。
By revising a K-NN classification method based on evidence theory, a new K-NN classification method based on evidence reasoning model is got, which made the classification result more accurate.
本文对基于证据理论的k - NN分类方法进行了修正，得到了基于证据推理模型的k - NN分类方法，使分类结果更加精确。
Based on the division of river-delta reservoir sedimentary facies, we present a distinguishing method based on the fuzzy reasoning NN.
针对河流-三角洲储层沉积微相的划分问题，提出了基于加权模糊推理神经网络的判别方法。
At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.
同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K - NN、BP神经网络和支持向量机分类器。
This paper introduces the background, features and key ideas of the NN real-time online control in NC process, and then analyzes the existing technical difficulty in this field.
介绍了神经网络实时监控数控加工技术产生的背景，详细分析了其特点和指导思想，并针对该研究领域目前存在的技术难题做了具体分析。
The numerical simulation results show that the semi-active suspension with MR damper using NN strategy is superior to those with traditional control or without any control.
半主动悬架的数值仿真结果表明，磁流变阻尼器半主动悬架的减振效果明显优于被动悬架以及其他控制方式和阻尼调节方式。
Then a genetic neural network for layout sub-problem is produced with GA and NN integrated together.
结合遗传算法，构造了布局子问题的遗传神经网络算法。
Compared with K-NN and ENN identity verification systems, the performance of verification system using improved ENN is enhanced.
实验表明，改进ENN的身份鉴别融合系统的认证率比K-NN和传统ENN融合系统有所提高。
The 1-Nearest-Neighbor Rule (1-NN) is the simplest and most natural classification rule.
最邻近法则（1-NN）是最简单和最为自然的分类法则。
The results show that the NN and GA can be used in structural damage identification system effectively.
结果表明，将神经网络和遗传算法用于结构损伤识别是有效的、可行的。
A fast method for spectrum analysis and interpolation using artificial neural network (NN) for the microwaves surveying system is studied.
本文研究了在微波探测系统中，利用人工神经网络做谱分析和插值的快速方法。
Then, base on the problem of attitude control of a satellite under development, we design a NN compensation controller for high accuracy orientation phase.
然后，基于某型小卫星的姿态控制问题，设计了高精度定向阶段的神经网络补偿控制器。
This paper presents a control scheme based on NN disturbance compensation for attitude control of satellite.
提出了一种基于神经网络扰动补偿的姿态控制方法。
NN: When you start with a hypothesis, you are dismissing a lot of other areas that might actually have an impact on whatever you are trying to figure out.
尼文•纳雷因：如果你从一个假设入手，你就排除了很多其他可能产生真正效果的领域。
The arithmetic of NN probability and seismic attribute analysis.
概率神经网络算法与地震属性分析。
A mixed NN model is constructed using BP algorithm improved with dynamic learning rate.
利用动态学习率改进BP算法，建立了混合神经网络模型。
Satisfactory results showed that NN can recognize different PD patterns successfully.
结果表明，神经网络能很好地识别局放模式。
The theory of identification model based on neural networks(NN)is to research into its capability of nonlinear approximation.
神经网络的非线性逼近能力的研究是神经网络成为辨识模型的理论基础。
ConclusionOrthogonal experimental results could be used to training BP-NN and the trained BP-NN could forecast the extraction results of active components in Chinese herb medicines.
结论可利用正交实验数据对BP网络进行训练，利用训练好的网络对中药药效物质基础的超临界萃取结果进行预测。
ConclusionOrthogonal experimental results could be used to training BP-NN and the trained BP-NN could forecast the extraction results of active components in Chinese herb medicines.
结论可利用正交实验数据对BP网络进行训练，利用训练好的网络对中药药效物质基础的超临界萃取结果进行预测。
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