建筑工程投标报价优选模型

通过建立区间二次规划数学模型、灰色模型、多目标规划等模型，建立材料价格和用量的选择模型，提供投标单位一种便捷的调整工程造价和控制造价的手段。     

利用多普勒信息的波达方向最大似然估计方法

为了充分利用信号的时域特性来改善信号波达方向（ＤＯＡ）的估计性能，本文从最大似然估计出发，推导出了有限快拍，低信噪比情况下多普勒信号波达方向的迭代估计计算法，为进一步减小运算量，本文还推导了一种简化算法，本文提出的两种算法对低信噪比，少快拍数下多普勒信号的ＤＯＡ估计性能比不利用时域特性的ＭＬ方法有明显改善，Ｍｏｎｔｅ－Ｃａｒｌｏ实验验证了本文方法的有效性。     

深亚微米条件下的多层VLSI／MCM层分配的遗传算法

本文提出了一个深亚微米条件下的多层ＶＬＳＭＣＭ有约束分层层分配的遗传算法。该算法分为两步：首先进行超层分配，使各线网满足Ｃｒｏｓｓｔａｌｋ约束，且超层数目最少；然后进行各超层的通孔最少化二分层。与目前的层分配算法相比，该遗传算法具有目标全面，全局优化能力强等特点，是一种可应用于深亚微米条件下的ＩＣ ＣＡＤ的有效分层方法。     

神经网络余／十转换的数学原理

本文提出了孙子定理的微分方程求解法，讨论了系数为求余算子的非线性微分方程的稳定平衡点和最佳解的误差。本文构造的非线性微分方程可以唯一地收敛于孙子定理的解，其误差可任意小。该微分方程可用人工神经网络实时计算，实现余／十转换。计算机模拟结果证实了本文理论的正确性。     

A review of robust design methods for multiple responses

Problems in engineering design often involve determining design variable settings to optimize individual product performance for multiple criteria, which are often in conflict. We review mathematically rigorous techniques from the statistical literature for finding a vector x of design variable settings, which produces an optimal compromise solution among a group of prioritized response variables. The best compromise solution is typically gained by optimizing an objective function, which incorporates the prioritized demands of multiple responses. Since most multi-response objective functions are constructed by combining the functions used to optimize univariate responses, a review of the prominent univariate approaches is presented first. A multivariate approach from the engineering literature called the compromise Decision Support Problem is also reviewed. Finally a table comparing the relative merits of the different multivariate approaches summarizes the article in a concise and user-friendly fashion.     

具多件内装物的瓦楞纸箱尺寸优化设计

跳出传统的设计思路，提出装多件内装物的瓦楞纸箱尺寸优化设计方法，建立优化设计模型，编写程序用于生产，节省纸用量，降低成本。     

采用基本门单元完全测试矢量的测试生成算法

文章介绍了一种采用基本逻辑门单元的安全测试矢量集生成测试矢量的方法，该方法可以将搜索空间限制在2(n 1）种组合内。它采用故障支配和故障等效的故障传播、回退等技术，建立了一套从局部到全局的测试生成新方法。同时，利用基本门单元安全测试矢量的规律性，可以实现最小的内存容量要求。在一些基准电路的应用实例中，得到了满意的结果。     

Optimal synthesis of tunable elastic wave-guides

Topology optimization, or control in the coefficients of partial differential equations, has been successfully utilized for designing wave-guides with precisely tailored functionalities. For many applications it would be desirable to have the possibility of drastically altering the wave-guiding properties of a device “on the fly,” in a controllable manner as an influence of some external input. This would enable wave-guides with highly non-linear input-output mappings, such as for example controllable wave switches.In this paper, we propose using finite elastic pre-straining for the purpose of tuning a wave-guide. In order to systematically formulate and solve the wave-guide synthesis problems we utilize mathematical programming methods in conjunction with topology optimization for parametrizing the design space. The resulting extremal problem is, from a practical point, equivalent to finding an optimal subdivision of a given control volume into two disjoint subsets occupied by two different materials, normally resulting in a highly heterogeneous elastic body with desired wave-guiding functionalities in the original and finitely deformed configurations.The proposed methodology is illustrated with numerical examples.     

Minimum-Energy Translational Trajectory Generation for Differential-Driven Wheeled Mobile Robots

Mobile robots can be used in many applications, such as exploration, search and rescue, reconnaissance, security, and cleaning. Mobile robots usually carry batteries as their energy source and their operational time is restricted by the finite energy available from the batteries. Therefore, energy constraints are critical to the service time of mobile robots. This paper investigates the minimum-energy control problem for translational trajectory generation, which minimizes the energy drawn from the batteries. Optimal control theory is used to find the optimal velocity trajectory in analytic form. To demonstrate energy efficiency obtainable, we performed simulations of minimum-energy velocity control and compared the results with loss-minimization control and energy-optimal trapezoidal velocity profiles. Simulation results showed that significant energy savings can be achieved, of up to 9% compared with loss-minimization control and up to 10% compared with energy-optimal trapezoidal velocity profile. We also performed an actual robot experiment using Pioneer 3-AT platform to show the validity of the proposed minimum-energy velocity control. The experimental results revealed that the proposed minimum-energy velocity control can save the battery energy up to 10% compared with loss-minimization control. Categories (3): Robot control, (5): RobotMotion Planning