邻近算法

计算结果表明，能明显缩短PCB的装配时间，优化效果较采用遗传算法和邻近算法更为明显。

The results show that the required time for mounting electronic parts can be decreased obviously , and it can resolve the problem more effectively than genetic algorithm or neighbor algorithm .

研究了非一体化供应链环境下的库存路径问题，给出改进的最邻近算法。

The inventory routing problem of decentralized supply chain was considered and a modified nearest algorithm was proposed .

利用线性判别分析，支持向量机和邻近算法分别对特征数据集进行分类学习，自动找出并正确标记新的测试图像中烟雾区域的位置，对比实验结果，找出最优分类算法。

Using LDA ( linear discriminant analysis ), SVM ( support vector machines ), KNN ( k-Nearest Neighbor algorithm ) to learn these characters , then mark the smoke region in the new testing image automatically . Compare experimental results , and find out the best classification algorithm .

关于DC函数最小化邻近点算法的注记

Remarks on the Proximate Point Algorithm for Minimization of DC Function

用线性四叉树成熟的Morton编码作为关键字来标识菱形块，发展了具有固定方向（fixedorientation）的块层次编码技术及邻近搜索算法。

The quadtree Morton code is used as the index for addressing the Diamonds and a hierarchical coding scheme of Diamonds is developed based on its fixed orientation .

邻近点算法（PPA）是求解单调变分不等式的一种常用的有效方法。

Proximal point algorithms ( PPA ) arc attractive methods solving monotone variational inequalities ( VI ) .

3使用Bregman函数的近似邻近点算法。

Approximate proximal point algorithm using Bregman function .

提出一种有别于传统聚类算法的邻近排挤算法对记忆细胞集进行不断的更新及删除，保证了Pareto最优解集的分布均匀性。

To assure the distribution of the Pareto optimal solutions set , a vicinity crowding algorithm different from the cluster algorithm was used to update the memory cells set .

对于寻找极大单调算子的零点，邻近点算法（PPA）是一种重要方法。

The proximal point algorithm ( PPA ) is an important method to find the zero points of maximal monotone operators .

本文首先介绍Chord分布式哈希查找机制，然后在此基础上分析改进方法：邻近路由算法和邻近邻居选择算法，最后指出了进一步研究的方向。

The paper firstly introduce the mechanism of decentralized hash lookup in Chord , then analyzes its betterment arithmetic , and finally proposes the direction that will further be studied .

2投影近似邻近点算法（PAPPA）。

Projection approximate proximal point algorithm ( PAPPA ) .

结果表明，分解算法的平均时间耗时量约是Bartholdi邻近搜索算法的23.66%。

The result is that average consumed time of this decomposing algorithm is about 23.66 % of Bartholdi 's.

然而精确地解子问题太昂贵有时也不可能，在许多文献里讨论了不精确邻近点算法（IPPA）。

However , solving the sub-problems is either expensive or impossible . The inexact proximal point algorithm ( IPPA ) was developed in many literature .

分析了球面Quaternary编码的特点，给出了三角格网方向判断的规则，并对该算法与Bartholdi邻近搜索算法的时间复杂度进行了对比。

The rule of distinguishing triangle direction is given out . The algorithm of neighbor finding from back to front with decomposing Quaternary code is presented . The analysis of time complexity between this decomposing algorithm and bartholdi 's algorithm is approached .

基于简单最邻近搜索算法的高维特征索引

The Indexing of High-Dimensional Features Using Simple Nearest Neighbor Search Algorithm

球面退化四叉树格网单元的邻近搜索算法

An Adjacent Searching Algorithm of Degenerate Quadtree Grid on Spherical Facet

K-邻近分类算法是个典型的分类算法。

K - Nearest Neighbour is a typical classification method .

极大单调算子的一个邻近点算法

A Proximal Point Algorithm of Maximal Monotone Operator in Reflexive Banach Spaces

求解两类问题的邻近点算法

Proximal Point Algorithm for Solving Two Kinds of Problem

求解单调变分不等式的近似邻近点算法的收敛性分析

The convergence analysis of an approximate proximal point algorithm for monotone variational inequalities

极大单调算子不精确邻近点算法的一种新的近似准则

A New Approximation Criterion for an Inexact Proximal Point Method for Maximal Monotone Operators

关于极大强单调算子的不精确邻近点算法的收敛性分析

On the Convergence Analysis of Inexact Proximal Point Algorithms for Maximal Strongly Monotone Operators

两类近似邻近点算法的比较及其推广

Comparison and Extension of Two Kinds of Approximate Proximal Point Algorithms for Monotone Variational Inequalities

本文主要研究用邻近点算法求解集值映射方程，变分不等式问题和最优化化问题。本文具体安排如下。

In this dissertation , we focus on adapting proximal point algorithms to solve set-valued equations , variational inequalities problems and optimization problems .

使用此方法可以为传统的光学邻近修正算法提供较为精确的迭代初值。

Better initial values for the iterative process of conventional model-based OPC algorithm can be provided by this method , with a little run-time penalty .

近年来，包括向前向后分裂算法，增广拉格朗日乘子法以及邻近点算法在内的一阶算法，已经吸引了越来越多的学者关注。

In recent years , the first-order algorithms such as " forward-backward splitting method "," augmented Lagrangian method ", or " proximal point algorithm " have attracted more and more attentions from the researchers .

第一章简要介绍了邻近点算法的基本框架和研究现状，最优化问题和变分不等式问题的背景和研究现状，以及本文需要用到的一些基本概念和引理。

It is organized as follows : In Chapter 1 , we introduce proximal point algorithms ' framework and current research situation , optimization problems and variational inequalities ' background and current research situation , and some basic concepts and lemmas , which are used in this dissertation .

根据目标做匀速直线运动的特点，仿真系统采用最简单、有效的最邻近数据关联算法进行数据关联，并应用扩展Kalman滤波算法进行目标状态估计。

The nearest neighbor data association algorithm is adopted in data association because of the uniform motion of target and extended Kalman filter is adopted to estimate target state to solve nonlinear filter .

不可微规划的邻近控制簇算法

A Proximity Control Algorithm in Bundle Methods for Nondifferentiable Minimization

本文研究了最邻近数据关联算法和多传感器检测融合的加权平均算法，为提高船舶交通量检测的准确率提供了有效手段。

This paper studies the algorithm of nearest neighbor in the data association and the algorithm of weight average in multi-sensor detection fusion .