查询词典 optimization

According to evaluation of the thermal, hydraulic, environmental and mechanic characteristics and energy performance of building and VAV air-conditioning system, and evaluation of the control performance of local control loops using the simulator of VAV system, this paper presents five on-line supervisory control strategies for local control loops: on-line optimization of VAV supply air static pressure set-point, on-line optimization of AHU supply air temperature set-point, on-line optimization of on/off set of CAV sub-system, on-line optimization of outdoor air set-point and on-line optimization of chilled water secondary pump pressure set-point.

通过数字仿真器对建筑物及其变风量空调系统的热力、动力、环境和能耗等运行特性的模拟，以及对系统常规采用的下位机控制回路可控性和稳定性等控制特性的研究和分析，本文先从局部的角度开展了系统局部优化的研究。提出并在仿真器上分别实施了VAV送风静压设定的实时优化，AHU送风温度设定的实时优化，CAV子系统开／停的实时优化，新风量设定的实时优化以及二级泵冷媒水供水压差设定的实时优化。

PSO is a population-based optimization algorithm, which mimics the social behavior of animals in a flock. It makes use of individual and group memory to update each particle position allowing global and local search optimization. The objective function considered was the total weight of the structure subjected to stresses, displacements and forces constraints. The effects of the parameters were investigated as well and such combination of tuning parameters promote a better global search behavior avoiding premature convergence while rapidly converging to the optimal solution. Results showed the effectiveness of the proposed method by comparing with ANSYS Design Optimization Tool (zero-order method). The PSO with the tuning parameters makes it an ideal method for offshore wind turbines foundations optimization tasks.(2) A reliability analysis method for pile foundation bearing axial loads based PSOThe performance function of pile foundation's axially bearing capacity sometimes is nonlinear and complex, on the basis of geometric meaning of structural reliability index, an optimum model with PSO for structural reliability analysis under arbitrary random variables was established, The PSO algorithm is very efficient to solve global optimization problemsIts use in structural reliability field presents not only the advantage of its facility of implementation, but also the possibility to obtain the design point and the failure probability with a good accuracy. In addition, PSO is a zero order algorithm, for no derivative is necessary for its implementation.

本文的研究针对桩式海上风机基础结构的特点，在国内外有关研究成果的基础上对海上风机基础结构优化设计理论和可靠度方法一些相关问题进行了较为深入的研究，具体做了以下几个方面的工作：(1)基于粒子群优化的桩式海上风机基础确定性优化设计方法桩式海上风机基础的优化设计是一个复杂的、非线性约束的优化问题，针对传统的基于梯度信息的优化方法在处理非线性问题中易陷入局部最优解的问题，本文将一种耦合惩罚函数的PSO算法引入到海上风机基础结构概念设计中，PSO算法是从群体动物聚集觅食这一活动中受到启发而发展的，该算法利用个体和群体的信息共享不断改进自身的位置从而进行局部和全局最优搜索，本文中以桩和三脚架连接段直径及壁厚为设计变量，以基础总重量作为优化的目标函数，在给定的约束条件下建立了三脚架基础优化数学模型，另外本文还研究了PSO参数变化对结果的影响，协调的参数组合可以避免陷入早熟收敛而能够快速的获得全局的最优解，通过与ANSYS优化模块的计算结果比较验证了该方法的有效性，本方法为海上风机基础的确定性设计提供了一条有效的途径。

The 5th chapter studied the crucial problem of floating detection application, develop the traffic flow information collection technology based on GPS, put forward the general principle and optimization method of the floating detection minimum sample size, and simulate several sample size scenarios of floating detection on the city road with the microscopic simulation software The 6th the combination application optimization of the dynamic traffic flow information collection technology, put forward the necessariness of combination application optimization, then analysed the principle and work steps of combination application optimization design, finally gived an example for the combination application optimization.

第五章是移动型检测器应用的关键问题研究。本章对移动型检测器的空间布置问题进行了研究，设计研究了基于GPS的动态交通流信息采集技术，提出了移动型检测器最小样本量确定的一般原则和方法，并利用微观仿真模拟软件进行了模拟分析。第六章是动态交通流信息采集技术组合应用优化设计研究。本章首先提出了进行动态交通流信息采集技术组合应用优化设计的必要性，然后分析了组合应用优化设计的原则，设计了组合应用优化设计的工作步骤，并举例分析了动态交通流信息采集技术组合方案的优化设计方法。

The 5th chapter studied the crucial problem of floating detection application, develop the traffic flow information collection technology based on GPS, put forward the general principle and optimization method of the floating detection minimum sample size, and simulate several sample size scenarios of floating detection on the city road with the microscopic simulation softwareThe 6th the combination application optimization of the dynamic traffic flow information collection technology, put forward the necessariness of combination application optimization, then analysed the principle and work steps of combination application optimization design, finally gived an example for the combination application optimization.

第五章是移动型检测器应用的关键问题研究。本章对移动型检测器的空间布置问题进行了研究，设计研究了基于GPS的动态交通流信息采集技术，提出了移动型检测器最小样本量确定的一般原则和方法，并利用微观仿真模拟软件进行了模拟分析。第六章是动态交通流信息采集技术组合应用优化设计研究。本章首先提出了进行动态交通流信息采集技术组合应用优化设计的必要性，然后分析了组合应用优化设计的原则，设计了组合应用优化设计的工作步骤，并举例分析了动态交通流信息采集技术组合方案的优化设计方法。

A fine-grained genetic algorithm based algorithm which is for the parameters optimization problem of agent model is proposed. The fine-grained genetic algorithm is used to solve the parameters optimization problem of agent model. As to the parameters optimization problem of the agents colony model, the first step is to define the concept of "the parameters mode of the combat agents colony" to describe the parameters of the combat agent colony model. Then the genetic algorithm is used to solve the optimization problem with the parameters mode of the combat agent colony model as the genetic individual. Besides the algorithm, the algorithm dispatch tactic is also considered. And the two level sequence dispatch tactic and the two level nesting dispatch tactic are put forward for those complex parameters optimization problem. At last, the model parameters optimization under antagonism codition is studied. The means to solve this problem is to translate it into a kind of antagonism problem, then use the competitive co-evolutionary genetic algorithms to solve it.

其中：提出了一种基于细粒度模型的作战智能体模型参数优化求解算法，用细粒度模型遗传算法求解作战智能体模型参数优化问题；提出了"作战智能体群体参数模式"的概念，对作战智能体群体模型参数进行形式化描述，再以作战智能体群体参数模式为遗传个体，应用遗传算法求解作战智能体群体模型参数的优化问题；研究了上述优化问题求解算法的调度策略，提出了分层模型参数优化算法的双层顺序调度策略和双层嵌套调度策略，解决复杂的模型参数优化问题；将对抗条件下作战模型参数的优化问题转化为一种对抗性问题，应用竞争性共同进化遗传算法，进行求解。

This paper determines the design idea of combining VISC with structural optimization design. Problems which existed in structural optimization design are analyzed and contents of optimization process are determined. Calling and dominating calculation program written in FORTRAN in the development environment of Delphi are realized by the techniques of FORTRAN/Delphi mixed-language programming and multi-threaded application. Parallel coordinates visualization technology is deeply researched and applied in software exploitation of optimization process. Essential programs of VISC software are compiled. Approaches which can improve efficiency of optimization are discussed. In the end, functional modules are integrated and a typical computational example is verified.

本文通过对结构优化设计和科学可视化的研究，确立了天线结构优化设计与科学计算可视化技术紧密结合的思路；根据天线结构优化设计的特点，针对优化设计中存在的问题，对系统结构优化的总体框架进行了分析和论述，确定了优化过程可视化的具体内容；通过FORTRAN与Delphi的混合语言编程实现了在Delphi环境下对FORTRAN计算程序的调控，充分利用了原有FORTRAN程序资源；对平行坐标技术进行深入研究，并将其应用于优化过程可视化模块的软件开发中，实现多维数据空间的可视化；编写优化计算过程可视化软件的核心程序；探讨了提高优化效率的途径；对基于可视化的天线结构优化设计软件系统进行集成，针对某天线进行了算例验证。

The traditional query tree optimization methods,parallel database optimization methods based on left linear trees and right linear trees,bushy trees,and operation of the forest,have their own pros and cons,they have been more in-depth and maturity of the study.The query optimization method based on multiple weighted tree has studied its model of parallel query plan,its complexity model of parallel query plan and query optimization algorithms.The semantic query method transforms an inquiry into one or several semantic equivalence inquiries then has to find and implement a strategy to achieve a better query.Agent-based parallel database query optimization using Multi-Agent technology to automatically search the integrity constraint conditions which are related to the determined query,there for,the efficiency between several relations' joins has been greatly improved.The parallel optimization algorithm,based on genetic algorithm which is suitable for multi-joins of cluster environment,has deeply studied the relations storage options,multi-joins query optimization and query processing and other key technologies based on cluster parallel database.

传统的查询树优化方法，即基于左线性树、右线性树、浓密树、操作森林的并行数据库查询优化方法，各有优劣，对其的研究比较深入、成熟；基于多重加权树的查询优化方法，研究了其并行查询计划模型、并行查询计划的复杂性模型和查询优化算法；语义查询优化方法将一个查询变换成一个或数个语义等价的查询，进而寻找并执行这些等价查询中具有较好实现策略的一个；基于Agent的并行数据库查询优化采用Multi-Agent技术自动查找与给定查询有关的完整性约束条件，使得多个关系间连接操作的效率得到很大的提高；基于遗传算法的并行优化算法，深入研究了基于机群并行数据库中关系存储的选择、多连接查询优化和查询处理等关键技术。

There exits several MDO algorithms. But they are in our opinion either nonefficient or complicated. So we devised an algorithm called Subspace Approximation Optimization . In the SAO algorithm, the whole system is decomposed into one system-level optimization and several disciplinary optimizations so that a large and complicated problem can be divided into several easy-solving sub-problems. The coupling relationships and the coordination among disciplines are presented by equality constraints and these equality constraints are assigned to relevant disciplines. The optimums of design variables in system level optimization are transferred to discipline level optimization. The optimums of design variables in discipline level correspond to the point that is the nearest to the optimums of design variables in system level. If the optimums of design variables in system level are out of feasible region of discipline 1eve1, linear constraints can be built in the system level optimization using the design variable optimums obtained by the discipline level optimization. The system level optimization would improve the design of the whole system with these linear constraints.

目前，国内外已经发展出了多种飞机多学科设计优化算法，本文的重点是针对协同优化算法的不足，提出了子空间近似优化算法(Subspace ApproximatingOptimization，SAO)，SAO算法中，整个系统的优化问题被分解成一个系统级优化和若干学科级优化，而各个学科之间的耦合与权衡关系则被当作等式约束，这些等式约束将被分配到各个学科级优化中去，系统级优化的任务是寻找整个系统的最优解，而学科级优化的目标函数是以系统级优化分配下来的设计点为圆心的超球半径的平方，因此，如果系统级优化分配下来的设计点在学科级优化可行域内，则学科级优化目标函数为0，反之，则学科级优化的最优点是系统级优化当前设计点距离可行域最近的点。

Corresponding to the unimodality of the vertical projection, a staged particle swarm optimization is proposed.

针对投影的局部单峰特性，提出分段适应粒子群优化(staged particle swarm optimization，SPSO)算法。

Then a BGPEOpt(BGP Egress Optimization Algorithm) algorithm is proposed to reduce the execution time of the typical algorithm by leveraging the .characteristics of cut link in the topology graph to reduce the frequency of recomputing traffic demand. Further more, mediate results are used in the iterative process to reduce the time of computing the IGP shortest distances from a source node to other nodes. Experimental results indicate that the running time of BGPEOpt reduced 7%~30% with the similar link utilization comparing to that of typical algorithms.

在此基础上，提出了静态阶段的BGP出口选择优化算法BGPEOpt(BGP Egress Optimization Algorithm)，BGPEOpt算法利用网络拓扑结构中割边的特殊性，减少流量矩阵重新计算的频率；同时利用算法在迭代过程中的中间结果，减少重新计算从一个源节点到其它节点最短路径的时间，从而提高了算法的时间性能。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。