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

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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Considering K Nearest Neighbor ( KNN) method has high accuracy but poor efficiency, this paper proposes a text categorization method based on the guidance of posterior probability named B-KNN.

针对K最近邻（KNN）方法分类准确率高但分类效率较低的特点，提出基于后验概率制导的贝叶斯K最近邻（B-KNN）方法。

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In this step, we use the strategy of combining the k nearest neighbor classifier and mutual information to judge if the two ROIs are visual similar.

在第二层的精筛阶段，利用最近邻分类器和互信息相结合的策略来度量两个ROI在视觉上是否相似。

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A method to predict the subcellular location of proteins is proposed based on the LZ complexity similarity of symbolic sequences and K nearest neighbor rule.

提出了一个基于符号序列LZ复杂性相似度和K近邻规则的蛋白质亚细胞位点类型预测的方法。

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K nearest neighbor query on moving objects based on road networks mainly has two challenges, manage efficiently moving objects position update and offer fast network distance calculations.

基于路网的移动对象K近邻查询主要有两个挑战，分别是有效地管理移动对象位置更新和提供快速的网络距离计算。

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This technology which combines Decision Trees and K Nearest Neighbor, can mine the relative similarity of latent-item in the course of case search.

该方法将决策树法和近邻检索法等数据挖掘技术相结合，对事例检索过程中必需的特征项相似度进行挖掘。

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At present, there are many pattern classification algorithms, mainly including bayes classifier, support vector machine, K nearest neighbor method and so on.

目前，模式分类的算法比较多，常用的有贝叶斯分类器、支持向量机、K近邻法等。

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In order to improve the efficiency and accuracy of search, the order of case retrieval is index, keyword and K nearest neighbor.

为了提高系统检索的效率和准确度，事例检索的方法按照索引、关键字、K最近邻法的顺序进行。

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This paper presents a modified K nearest neighbor ( MK NN) track correlation algorithm applying to distributed multisensor data fusion.

提出一种适合于分布式多传感器数据融合的新的航迹相关算法（MK－NN）。

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In this paper we develop an efficient method in order to process k nearest neighbor queries ( K-NN) in a mobile environment.

本文提出了一个以处理动态环境下的K个最近邻居（K-NN）查询问题的有效的方法。

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Searches based on content similarities in large multimedia libraries are essentially K nearest neighbor searches in high dimensional spaces.

大容量多媒体数据库的基于内容相似性的检索本质上是高维特征空间中一定距离函数的K近邻问题。

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Several major flow pattern identification methods are introduced: nearest neighbor method, K nearest neighbor, neural network and feature extraction method.

介绍了流型辨识的几种主要的方法：最近邻法、K近邻算法、神经网络法和特征提取法。

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Therefore, moving object index strategy and K nearest neighbor query strategy need to be studied.

因此需要研究基于路网的移动对象索引策略和K近邻查询策略，如何采用快速、有效的方法来处理移动对象K近邻查询是一个具有挑战性的研究课题。

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Two-tier K Nearest Neighbor Algorithm Based on Active Diagnostic Recommendation

基于主动诊断推荐的双层K-最近邻算法

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