基于极值动力学的自组织优化算法求解TSP问题

旅行商问题(traveling salesman problem, TSP)具有很强的理论研究和工程应用价值. 在定义离散状态变量和局部适应度的基础上, 分析了TSP优化解的微观特征; 将自组织临界(self-organized criticality, SOC)的概念引入到组合优化领域, 提出了一种基于极值动力学的自组织优化算法. 该算法利用快速下降和间断涨落的动态搜索过程, 高效地遍历解空间中的局部最优解. 针对TSPLIB中典型实例, 计算结果表明其求解效率和优化性能均优于模拟退火和遗传算法等优化方法. 文中算法提供了一种全新的思路, 有助于从系统角度理解组合优化问题的复杂性, 并分析合理的优化动力学过程.     

OCL约束验证与实现的方法

为了能在运行时验证OCL约束,提出了约束验证框架.针对OCL-Java代码(即OCL约束对应的可执行Java代码)插入的简单方案和封装方法存在的不足,给出了改进的代码插入方案,其中应用异常处理技术从而能够捕获冲突的约束.为了使OCL-Java代码根据设计的代码模式插入到Java程序中,对Java解析器作了修改.最后,实验结果表明了该方法的可行性.     

基于卟啉传感器的气体检测系统的设计

针对传统气体检测方法的不足,设计了一种基于卟啉传感器的快速气体检测系统.反应室的流体仿真表明该系统检测结果具有可比性.该系统采集存储卟啉传感器与气体反应前后的图像,通过图像处理技术获得传感器阵列的颜色变化信息,将其与数据库中的记录进行匹配,得到检测结果.实验表明:该系统响应快速,能准确检测识别多种有害气体.     

利润-CVaR准则下的二级供应链定价与订货策略研究

传统的定价与订货策略研究多是建立在风险中性的假设之上,近来也有利用风险度量CVaR研究风险厌恶对库存的影响.因此,以期望利润和CVaR的加权平均为目标函数,研究零售商的订货策略,并在此基础上研究上游供应商的定价策略.这样的利润-CVaR目标既反映了决策者追求高利润的愿望,又反映了其对潜在风险的控制.     

基于C8051F340控制的TD直放站控制方案设计

介绍一种基于C8051F340快速单片机控制的直放站设计;采用GPS同步法,按时隙功率控制,自动增益控制AGC环路,系统的非线性指标良好、抗干扰性强、可靠性高.比以功率检测的同步方法和基于特征窗搜索的同步方法实现简单,应用范围更广,可用于任何无线直放站应用场合,特别适用于干放及无线射频交换场合.     

新型国产近红外分析仪的菜籽菜粕快速检测技术研究

近红外光谱分析作为1种快速无损的绿色分析技术,可应用于检测油料原料和油脂产品品质,为粮油企业带来巨大经济效益.本文采用一款新型国产化的近红外漫反射光谱分析仪对菜籽和菜粕进行了检测分析,分别对菜籽的水分、蛋白、含油量、脂肪酸、硫苷含量和菜粕水分、蛋白和含油量指标建立模型并验证.结果显示近红外检测结果与国标参考方法检测结果相关性好、准确度高.表明新型国产化的近红外分析仪可满足油脂企业对菜籽和菜粕产品的质量控制要求.     

超空泡水下航行器定深控制研究

极高的航速使得对超空泡水下航行器的控制变得异常复杂. 为了对其深度进行有效控制, 必须对其纵平面运动特性进行研究. 本文首先建立了超空泡水下航行器的纵平面运动模型, 分析了其纵平面运动特性; 然后进行了控制算法的综合; 最后, 仿真及试验结果均验证了所设计的航行器纵平面运动控制算法的有效性. 试验结果表明该控制系统具有较高的控制精度. 本文的研究成果为进一步研究水下超空泡航行器的运动控制提供了必要的理论基础.     

Effective multiplicative updates for non-negative discriminative learning in multimodal dimensionality reduction

Fisher discriminant analysis gives the unsatisfactory results if points in the same class have within-class multimodality and fails to produce the non-negativity of projection vectors. In this paper, we focus on the newly formulated within and between-class scatters based supervised locality preserving dimensionality reduction problem and propose an effective dimensionality reduction algorithm, namely, Multiplicative Updates based non-negative Discriminative Learning (MUNDL), which optimally seeks to obtain two non-negative embedding transformations with high preservation and discrimination powers for two data sets in different classes such that nearby sample pairs in the original space compact in the learned embedding space, under which the projections of the original data in different classes can be appropriately separated from each other. We also show that MUNDL can be easily extended to nonlinear dimensionality reduction scenarios by employing the standard kernel trick. We verify the feasibility and effectiveness of MUNDL by conducting extensive data visualization and classification experiments. Numerical results on some benchmark UCI and real-world datasets show the MUNDL method tends to capture the intrinsic local and multimodal structure characteristics of the given data and outperforms some established dimensionality reduction methods, while being much more efficient.     

Structure design and fabrication of a novel dual-mass resonant output micromechanical gyroscope

A novel dual-mass resonant output micromechanical gyroscope is proposed which utilizes resonant sensing as the basis for Coriolis force detection instead of displacement sensing. It can overcome the shortcoming of single-mass resonant output micromechanical gyroscope and can reduce the common mode acceleration error by using a dual-mass topology structure and lever differential mechanism. The structure and operating principle of the device are introduced. Moreover, some important theoretical analyses of the gyroscope are provided in detail. The analytical results have shown that the resonant frequencies of vibrating mass and double-ended tuning fork resonators are 3.153 and 62.853 kHz. The device has a frequency sensitivity of 12.535 Hz/deg/s and a mechanical noise floor of $ 7.957\deg /{\text{h}}/\sqrt {{\text{Hz}}} A novel dual-mass resonant output micromechanical gyroscope is proposed which utilizes resonant sensing as the basis for Coriolis force detection instead of displacement sensing. It can overcome the shortcoming of single-mass resonant output micromechanical gyroscope and can reduce the common mode acceleration error by using a dual-mass topology structure and lever differential mechanism. The structure and operating principle of the device are introduced. Moreover, some important theoretical analyses of the gyroscope are provided in detail. The analytical results have shown that the resonant frequencies of vibrating mass and double-ended tuning fork resonators are 3.153 and 62.853 kHz. The device has a frequency sensitivity of 12.535 Hz/deg/s and a mechanical noise floor of 7.957deg/\texth/?{\textHz} 7.957\deg /{\text{h}}/\sqrt {{\text{Hz}}} in air. The finite element simulation results verify the accuracy of analytical algorithms. The common mode acceleration error of device can be reduced by 97.6%. The device is fabricated by SOG (Silicon on Glass) micro fabrication technology. Some important performances are measured by experimental method. The micromechanical gyroscope can be used to estimate the rotation rate by further implementing the signal processing electronics.     

稀土萃取过程组分含量的RBF软测量建模

稀土萃取分离过程的自动控制一直是稀土工业急待解决的关键难题,要实现稀土萃取分离过程的自动控制,首先必须解决串级萃取槽中各稀土组分含量的在线检测,而传统的检测又有很大的问题,软测量技术在稀土萃取过程控制中的应用研究开始活跃起来。该文是基于RBF网络的稀土萃取过程组分含量进行软测量建模的研究。