partitioning algorithm meaning in Chinese
分区算法
Examples
- By analysis the instance of complete - point and bi - partition point , the thesis presents two merge rules to improve the partition algorithm given by c . j . tseng . the experiments show the pedition results improved notably by using the revised algorithm
文中通过分析完全点和二分点的情况，提出了两个合并准则，对于c . j . tseng提出的、目前使用广泛的基团剖分算法进行了改进。 - With the booming of the requirement of network management , network intrusion detection arid qos , a new fast scalable multi - dimension packet classification algorithms , based on pcbnp , rfc and regional partition algorithm , is given in this paper
该算法通过压缩、分割和索引操作，设计了压缩分割规则表和索引列表结构表这两类数据存储结构，能支持上万条多维分类规则，分类速度快、存储空间小、支持快速更新。 - One of the main problems in pdes is how to partition the network simulation workload to decrease the time needed to complete the simulation and improve performance of simulation . here a new optimized partition algorithm was put forward , which first analyses the performance factors of parallel simulation and then constructs a performance estimation model for partition ; based on this model , it mends the graph partition algorithm to consider all factors , including simulation applications and simulation environments . optimized factors are workload balance 、 communication cost and time window of lookhead
鉴于基于传统图划分算法的任务划分工具存在诸多不足,本文提出了并行网络模拟任务的优化划分方法,其思想是:首先从pdes机制出发,分析影响并行网络模拟性能的各种因素并建立一个能够综合考虑各种因素的并行网络模拟性能估计模型;其次,改进多级图划分算法,使得算法具有综合考虑模拟应用与模拟运行环境,同时在优化过程中使用性能估计模型指导划分,实现对影响并行网络模拟性能的三个因素(包括负载均衡、通信开销、安全时间窗口长度)的优化能力;最后,结合并行网络模拟性能估计模型与改进的多极图划分算法,实现了并行网络模拟任务的优化划分。 - In this dissertation , the research trends for the problem have been introduced ; the ‘ dim ’ and ‘ point ’ has been strictly defined in mathematics from machine vision and human vision ; the ideal clutter suppression system based on clutter predication and the realization and evaluation of evaluation index has been studied , in succession the clutter suppression technologies have been researched . firstly , the classic nonparametric algorithm has been analyzed in detail and systematically , for it ’ s weakness that it cannot remove the non - stationary clutter ideally , kalman filter algorithm for clutter suppression in 2d image signal has been built . secondly , fast adaptive kalman filter is presented based on fast wide - sense stationary areas partition algorithm : limited combination and division algorithm based on quarti - tree algorithm , new taxis filter route algorithm which can break through the limitation of the necessity of pixel neighborhood of 2d filter and laplace data model with two parameters which is perfectly suitable for the residual image of kalman clutter suppression
首先分析了经典的非参数法,对于四种具有代表性的核,从前述的三个性能评价方面做了分析和对比,指出了其速度快的优点和对非平稳图像适应性差的弱点,针对非参数法的弱点,重点研究了对非平稳图像适应良好的卡尔曼杂波抑制技术:建立了非平稳图像的类自回归模型,在此基础上建立了二维卡尔曼滤波基础的两个方程:状态方程和测量方程;建立了非平稳图像准平稳区域快速划分算法:基于四叉树法的有限分裂合并算法;二维空间的基于k排序的滤波路线算法,突破了空域滤波路线上区域相邻的限制;在这些研究的基础上实现了快速卡尔曼估计,实验验证了该方法相对逐点卡尔曼估计可以提高运算速度三倍左右;杂波抑制结果表明传统的高斯性检验并不适合卡尔曼估计后的残余图像,由此建立了残余图像的双参数拉普拉斯模型,实验表明其可以完好的吻合残余图像的概率密度曲线。 - The training method is very important to hmm based approaches , a new model training method based on genetic algorithm is also discussed at the end . and in chapter 5 , a fuzzy rule based recognition method is proposed . it is heavily rely on a new feature space partition algorithm , in which a modified fuzzy clustering method is used
首先，研究了一种基于模糊聚类的特征空间划分方法以及一种隶属度函数的优化算法；然后讨论了一种新的模糊规则提取算法，用于提取合理的分类规则；为了有效地构造基于模糊规则的分类器，引入了一种网络模型，使用该网络可以有效地实现一个模糊规则系统；在此基础上，构造了具有实用价值的识别系统。