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 graph partitioning problem 的翻译结果: 查询用时：0.008秒
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 graph partitioning problem 图划分问题(4)
 图划分问题
 A parallel algorithm based on the neural network is presented and used to solve the graph partitioning problem. 文中给出了一种基于神经网络求解图划分问题的并行算法； 短句来源 Half edge and its assembly can represent various constraints,Machine redundant manufacturing cell design convert to a combination optimal problem based on half edge graph,multi-way half edge graph partitioning problem with redundant plan paths. 用半边及其结合性表示各种局部约束,将机器可选制造单元设计问题转化为基于半边图的组合优化问题,即计划路径可选的半边图划分问题。 短句来源 Multi-way half edge graph partitioning problem with redundant plan paths is the complex combination optimizm problem that has various constraint. 计划路径可选的半边图划分问题是一类含有多种局部约束的复杂组合优化问题。 短句来源 Having Designed an extrude intake algorithm for the half edge graph partitioning problem,this algorithm can solve machine redundant manufacturing cell design problem. 设计了针对半边图划分问题的半边图挤出吸入算法,用此算法求解了机器可选制造单元成组设计问题。 短句来源
 “graph partitioning problem”译为未确定词的双语例句
 GENERAL IMPROVING GENETIC ALGORITHM FOR SOLVING MULTI WAY GRAPH PARTITIONING PROBLEM 一种通用的求解图的多划分问题的改进遗传算法 短句来源 The latter describes the basic method of neurocomputation,and illustrates some optimization problems mapped to neural networks including traveling salesman problem,graph partitioning problem etc. 后者论述了神经网络求解优化问题的基本方法,并例举了旅行商、图的划分等优化问题的神经网络求解方法. 短句来源 Analyzed the characteristics of multi way graph partitioning problem, a general improving genetic algorithm which is suitable for solving the problem of the kind is presented. 针对图的多划分问题的特点 ,本文提出了一种适合于求解这一类问题的改进遗传算法 . 短句来源 Shi and Malik converted image segmentation into graph partitioning problem and proposed the normalized cut criterion. Rather than focusing on local features and their consistencies in the image data, this approach aims at extracting the global impression of an image. Shi和Malik将图像分割转化为图的划分问题,提出了归一化割准则,这种分割方法没有把局部特征和一致性度量作为解决问题的关键,而是着重于提取整幅图像的特征,因此取得了较好的分割结果。
 相似匹配句对
 [s,t]-GRAPH [s,t]-图及其Hamilton性 短句来源 A Stochastic Algorithm for Graph K-Partitioning 一种图K划分的随机算法 短句来源 The Optimization of k-Unicyclicly Partitioning a Graph 图的k-单圈划分中的优化问题 短句来源 The problem of partitioning a graph has been long concered. 图的划分问题曾引起图论界的广泛关注. 短句来源 Graph Theory. Graph Theory。 短句来源

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 graph partitioning problem
 This paper describes an empirical study of the performance of various local search heuristics for thisk-way graph partitioning problem. The graph partitioning problem consists of dividing the vertices of a graph into clusters, such that the weight of the edges crossing between clusters is minimized. When the NP hard graph partitioning problem is formulated as a continuous quadratic programming problem, the constraints have this structure. In the graph partitioning problem, as in other NP-hard problems, the problem of proving the existence of a cut of given size is easy and can be accomplished by exhibiting a solution with the correct value. The simple graph partitioning problem is to partition an edge-weighted graph into mutually disjoint subgraphs, each consisting of no more than b nodes, such that the sum of the weights of all edges in the subgraphs is maximal. 更多
 This paper contains two parts:neurocomputing theory and case studies. The former deuls with some basic concepts of the computation, digital computation, analogy computation, biology computation, neurocomputation, computational energy and optimization theory. The latter illustrates some combinatorial optimization problems mapped on to neural networks including traveling salesman problem, graph partitioning problem, graph vertex cover problem, graph independent set problem,graph... This paper contains two parts:neurocomputing theory and case studies. The former deuls with some basic concepts of the computation, digital computation, analogy computation, biology computation, neurocomputation, computational energy and optimization theory. The latter illustrates some combinatorial optimization problems mapped on to neural networks including traveling salesman problem, graph partitioning problem, graph vertex cover problem, graph independent set problem,graph maximum clique problem, graph maximum matching problem, graph isomorphism problem, task assignment problem, eight queen problem, A/D converter problem, decomposition/decision problem,linear programming problem and job-shop scheduling problem etc. 本文可分为两大部分:神经计算理论及其在组合优化问题中的应用.前者涉及到计算、数字计算、模拟计算、神经计算的基本概念,计算能量和优化方法;后者列举了旅行商、图的划分、覆盖、最大独立集、最大集团、最大匹配、同构、着色、任务分配、八皇后、模拟数字转换、分解/判定、线性规划和作业调度等组合优化问题的神经网络求解方法. Introduces heuristic search techniques and neurocomputing techniques for solving optimization problems. The former deals with the principles and features of the four common kinds of heuristic search techniques. The latter describes the basic method of neurocomputation,and illustrates some optimization problems mapped to neural networks including traveling salesman problem,graph partitioning problem etc. At last,this paper summarizes these two methods,i. e. the AI's method and the neurocomputational method,and... Introduces heuristic search techniques and neurocomputing techniques for solving optimization problems. The former deals with the principles and features of the four common kinds of heuristic search techniques. The latter describes the basic method of neurocomputation,and illustrates some optimization problems mapped to neural networks including traveling salesman problem,graph partitioning problem etc. At last,this paper summarizes these two methods,i. e. the AI's method and the neurocomputational method,and points out further research directions. 本文介绍优化问题求解的启发式搜索技术及优化问题的神经网络求解技术.前者论述了目前常见的四类启发式搜索技术的原理,并讨论了各类技术的特点;后者论述了神经网络求解优化问题的基本方法,并例举了旅行商、图的划分等优化问题的神经网络求解方法.最后,本文对优化问题求解的启发式搜索和神经网络方法作了比较,并指出了针对这二种方法的进一步研究方向. In this paper, the artificial neural network is proposed for the partitioning problem in telecommunication network design.A parallel algorithm based on the neural network is presented and used to solve the graph partitioning problem. The parallel algorithm was tested by some randomly generated examples including up to 100-vertex problem.Computer simulation results show that the parallel algorithm finds better solutions than the heuristic algorithm within fifteen iterationn steps. 本文应用神经网络研究通信网设计中的划分问题。文中给出了一种基于神经网络求解图划分问题的并行算法；该算法验证了一些随机生成的例子（包括高达１００个顶点的问题）。计算机模拟结果表明该算法在１５步迭代之内求得较好解，优于传统的启发式算法。 << 更多相关文摘
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