二维参数化图形技术研究进展

近几年来，参数化图形技术得到了不断的发展。目前已有多种参数化图形方法及系统。这些参数化图形方法可分为３种，即变分几何法、几何推理法和过程法。主要介绍这３种方法的研究进展。     

基于梯度投影法与随机优化算法的约束优化方法

针对带有线性等式和不等式约束的无确定函数形式的约束优化问题,提出一种利用梯度投影法与遗传算法、同时扰动随机逼近等随机算法相结合的优化方法。该方法利用遗传算法进行全局搜索,利用同时扰动随机逼近算法进行局部搜索,算法在每次进化时根据线性约束计算父个体处的梯度投影方向,以产生新个体,从而能够严格保证新个体满足全部约束条件。将上述约束优化算法应用于典型约束优化问题,其仿真结果表明了所提出算法的可行性和收敛性。     

基于约束关系的变强度组合测试用例集生成算法

针对传统的变强度组合测试方法对系统中各因素之间的约束关系考虑不足,从而可能导致测试用例冗余的问题,论文提出了一种基于one-Test-at-a-time策略的变强度组合测试用例集生成算法,该算法充分考虑了因素间的约束关系,从而在一定程度上减少了测试用例集的规模。最后通过实验验证了算法的可行性和有效性。     

造价工程师激励约束机制建立研究

基于工程造价活动专业性强的特点和造价工程师的执业特点,从造价工程师需求角度分析,提出建立造价工程师物质激励、社会认知激励的激励机制和建立造价工程师责任追究制度、信用评价体系、行业自律制度的风险约束机制。     

多目标资源受限项目调度的多种群蚁群算法

为实现资源受限项目调度的多目标优化,通过改进传统蚁群算法,提出适用于多目标优化的多种群蚁群算法.该算法基于串行进度生成机制,每个蚁群具有各自的目标函数、与目标函数相匹配的不同搜索策略以及各自的信息素更新机制.各蚁群独立进行搜索决策,但各蚁群之间存在信息素的相互作用,从而实现加速搜索.针对多目标资源受限项目调度问题设计新的精英策略.在目标规划基础上构造一系列多目标项目调度算例,经系统测试表明,所提出的多种群蚁群算法能够有效优化资源受限项目的资源配置,实现多目标优化.     

刚体动力学初值问题的拟变分原理及其应用

随着科学技术的发展,对刚体动力学提出新的要求.应用变积方法,建立了刚体动力学初值问题的拟变分原理.推导出刚体动力学初值问题的拟变分原理的拟驻值条件.建立了刚体动力学初值问题的广义拟变分原理,说明了应用广义拟变分原理求得问题的解析解和数值解的途径.借助算例说明了应用变分方法来研究刚体动力学初值问题的优越性.     

Equilibrium equations for nonlinear buckling analysis of drill-strings in 3D curved well-bores

With the development of drilling technology, the oil/gas well has evolved from its early vertical straight form to the inclined, horizontal, plane curved, or even 3D curved well-bore. Understanding of the buck-ling behavior of a drill-string in a well-bore is crucial for the success of a drilling operation. Therefore, equilibrium equations for analyzing the buckling behavior of a drill-string in a 3D curved well-bore are required. Based on Love’s equilibrium equations for a curved and twisted rod in space, ...     

结合相似性拟合与空间约束的图像分割

目的 图像中的目标一般含有很多子类,仅仅利用某个子类的特征无法完整地分割出目标区域。针对这一问题,提出一种结合相似性拟合与空间约束的图像交互式分割方法。方法 首先,通过手工标记的样本组成各个目标的字典,通过相似度量搜寻测试样本与各个目标的字典中最相似的原子建立拟合项;再结合图像的空间约束项,构建图像分割模型;最后利用连续最大流算法求解,快速实现图像分割的目的。结果 通过对比实验,本文方法的速度比基于稀疏表示的分类方法的速度提高约13倍,而与归一化切割(N-Cut),逻辑回归(logistic regression)等方法相比,本文方法能取得更稳定和准确的分割结果。此外,本文方法无需过完备字典,只需要训练样本能体现各个子类的信息即可得到稳定的图像分割结果。结论 本文交互式图像分割方法,通过结合相似性拟合以及空间约束建立分割模型,并由连续最大流算法求解,实现图像的快速准确的分割。实验结果表明,该方法能够胜任较准确地对自然图像进行分割以及目标提取等任务。     

MABP: an optimal resource allocation approach in data center networks

In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.     

Research progress on water resources management theory of “basing four aspects on water resources”EI北大核心CSCD

In order to implement the rigid constraint system for water resources and promote refined management of water resources, based on the analysis of the concept and notion of “basing four aspects on water resources” and the summary of the experience of water resources management, the basic theory and management guidelines for water resources control of “basing four aspects on water resources” are proposed. The latest progress of “ basing four aspects on water resources” is systematically sorted out, and it is pointed out that further research on the water resources control of “basing four aspects on water resources” should be deepened from the aspects of macro-system evaluation system construction, water resources optimization allocation model reconstruction, and refinement of water resources control system. © 2023, Editorial Board of Water Resources Protection. All rights reserved.