计及励磁电流谐波的同步发电机空载电势分析

采用多回路理论,研究了同步发电机空载时计及励磁电流谐波的定子谐波电势,得到该情况下定子低次谐波电势的计算公式,并附有计算实例．     

冗余技术在炮弹涂油机可靠性设计中的应用

运用冗余技术于军械装备的可靠性设计之中,可大大提高装备的可靠性。总结了炮弹涂油机可靠性设计的经验,从理论和实践的结合上阐述了冗余技术运用的途径、方法和注意的问题,通过给出涂油机可靠性模型、可靠性结构函数、计算单元重要度和系统的可靠性,为可靠性设计提供了一个简便的范例。     

确定车削加工工艺系统刚度的一种实验方法

将工艺系统的弹性变形看成是由平移和弯曲两种变形构成,利用阶梯形工件,可以确定工艺系统的等效刚度。从而为合理地选择加工参数、保证加工质量提供必要的条件。     

Production scheduling with history‐dependent setup times

We consider a parallel‐machine scheduling problem with jobs that require setups. The duration of a setup does not depend only on the job just completed but on a number of preceding jobs. These setup times are referred to as history‐dependent. Such a scheduling problem is often encountered in the food processing industry as well as in other process industries. In our model, we consider two types of setup times—a regular setup time and a major setup time that becomes necessary after several “hard‐to‐clean” jobs have been processed on the same machine. We consider multiple objectives, including facility utilization, flexibility, number of major setups, and tardiness. We solve several special cases assuming predetermined job sequences and propose strongly polynomial time algorithms to determine the optimal timing of the major setups for given job sequences. We also extend our analysis to develop pseudopolynomial time algorithms for cases with additional objectives, including the total weighted completion time, the total weighted tardiness, and the weighted number of tardy jobs. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

引导学生积极参与数学课堂学习的探索与实践

树立新理念,创建和谐学习情境,唤醒学生的主体意识,让学生在积极的思维和情感活动中主动地参与教学过程就越来越显现出其重要性了,这也是新课程改革给我们提出的最基本的要求。本文从兴趣引路,激发学生主动参与的积极性;营造民主和谐的氛围,创造学生主动参与的环境;开展小组合作学习,构建学生主动参与的平台;体验成功的愉悦,培养学生的创新能力;正确运用评价,树立学生主动参与的信心等五个方面,阐述了在数学课堂教学中如何让学生主动参与学习。     

当代教师的基本素养

随着社会对人才培养质量要求的提高,对教师的素质有了更高的要求,要求当代教师具备教学反思的能力、终身学习的理念、执着的教育追求、高度的责任感、仁爱之心、宽容的情怀等基本素养。     

一种基于改进Hausdorff距离的图像匹配方法

Hausdorff距离(HD)是图像匹配常用的相似性准则。针对HD在实际图像中难以匹配的问题,提出了基于核密度函数的HD改进形式,该HD是通过对各个最小距离值进行核密度函数计算,并将函数值的和的均值作为单向HD值,无向的HD值取两个单向值的最小值。实验结果表明,提出的改进HD在遮挡、局部变化情况下比其它的HD距离具有较好匹配效果。     

Scheduling and lot streaming in two‐machine open shops with no‐wait in process

We study the problem of minimizing the makespan in no‐wait two‐machine open shops producing multiple products using lot streaming. In no‐wait open shop scheduling, sublot sizes are necessarily consistent; i.e., they remain the same over all machines. This intractable problem requires finding sublot sizes, a product sequence for each machine, and a machine sequence for each product. We develop a dynamic programming algorithm to generate all the dominant schedule profiles for each product that are required to formulate the open shop problem as a generalized traveling salesman problem. This problem is equivalent to a classical traveling salesman problem with a pseudopolynomial number of cities. We develop and test a computationally efficient heuristic for the open shop problem. Our results indicate that solutions can quickly be found for two machine open shops with up to 50 products. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Single machine parallel batch scheduling subject to precedence constraints

We consider the single machine parallel batch scheduling problems to minimize makespan and total completion time, respectively, under precedence relations. The complexities of these two problems are reported as open in the literature. In this paper, we settle these open questions by showing that both problems are strongly NP‐hard, even when the precedence relations are chains. When the processing times of jobs are directly agreeable or inversely agreeable with the precedence relations, there is an O(n²) time algorithm to minimize the makespan. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

基于改进核极限学习机和集成学习理论的目标机动轨迹预测

为了提高目标轨迹预测的精度以及预测模型的泛化能力,提出基于改进蝙蝠算法优化的核极限学习机(Kernel Extreme Learning Machine,KELM)和集成学习理论目标机动轨迹预测模型。构建KELM模型,并采用改进的蝙蝠算法对KELM的参数进行优化;以优化后的KELM神经网络为弱预测器,结合集成学习算法生成强预测器,通过训练不断优化强预测的结构和参数,得到一种基于集成学习理论的目标机动轨迹预测模型;基于不同规模的样本,将所得预测模型与逆传播神经网络、支持向量机和极限学习机等模型进行对比分析。仿真结果表明:所提目标机动轨迹预测模型具有较好的预测精度和泛化能力。