An algorithm for continuous reverse k-nearest neighbor queries of moving objects in road network

Development and improvement of K-Nearest Neighbor clustering technique

K-最近邻分类技术的新发展与技术改进

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Study on segmentation method for multi-spectrum head MRI based on fuzzy k-nearest neighbor rule

基于模糊K-近邻规则的多谱磁共振脑图像分割方法的研究

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Multi-feature fusion method based on support vector machine and k-nearest neighbor classifier

基于支持向量机和k-近邻分类器的多特征融合方法

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A Method Research on Active Defence Technology against Virus Based on K-Nearest Neighbor Algorithm of Kernel

基于核的K-最近邻算法的主动式防御研究

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A k-Nearest Neighbor Classification Rule Based on the Transferable Belief Model

基于可传递信度模型的k-NN分类规则

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Realization of k-Nearest Neighbor Decision Rule With A Boolean Neural Network

k-最近邻判别法的一种布尔神经网络实现

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Academic Text Classification Based on K-Nearest Neighbor Method

基于K-近邻方法的科技文献分类

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Incremental Hypertext Classification Based on Fuzzy K-Nearest Neighbor and Evidence Theory

基于模糊K最近邻和证据理论的增量式超文本分类方法

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A new fuzzy k-nearest neighbor codebook design algorithm of vector quantization

一种新的模糊K邻域矢量量化码本设计算法

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A Particle Swarm Optimization Based Rapid K-Nearest Neighbor Classification Algorithm

基于微粒群优化的快速K-近邻分类算法

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An application of K-nearest neighbor algorithm for the teaching of web page classification

K近邻算法在教学网页分类中的应用

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Computer Virus Detection Based on Improved K-Nearest Neighbor Algorithm

基于改进的K-最近邻算法的病毒检测方法

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Application of Fuzzy ART in the K-Nearest Neighbor Classification Algorithm

基于Fuzzy ART的K-最近邻分类改进算法

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Application Study of Segmentation Algorithm of Head MRI Based ON K-Nearest Neighbor Rule

基于K-最近邻规则的磁共振颅脑图像分割算法的应用研究

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Design and Implementation of Web Page Automation Classification System Based on K-Nearest Neighbor Algorithm

基于K-近邻算法的网页自动分类系统的研究及实现

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A Gradual Chinese Text Classification Technology Based on the k-nearest Neighbor Method

基于k-近邻方法的渐进式中文文本分类技术

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In order to reduce the effect of dielectric coefficient and magnetic inductive capacity on pipeline robot's localization, an N order K nearest neighbor ( K-NN) electromagnetic wave localization algorithm is presented.

为了减小传输介质介电常数、磁导率参数对管道机器人定位的影响，提出了N次K-NN分类算法。

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The statistic approaches, for example, distance, Fisher, k nearest neighbor, wise linear classifiers, fail to solve multi regional distributions such as the alternate table problems.

当处理同类别多区域样本分布问题，例如变标签问题时，距离判别、Fisher判别、k-近邻分类、分段线性分类等统计分析方法遇到困难。

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This paper presents an algorithm based on the combination of Support Vector Maching ( SVM) and k Nearest neighbor ( k NN), to deal with ambiguities in Chinese word segmentation.

本文提出了基于支持向量机（SVM）和k近邻（kNN）相结合的一种分类方法，用于解决交集型伪歧义字段。

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We measure the importance of bins on some level by K nearest neighbor entropy, then we remove those bins whose k nearest neighbor entropy bigger than threshold.

我们通过K近邻信息熵来衡量某个层次上格子的重要程度，并移除那些K近邻信息熵大于此层次阈值的格子。

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