B-learning在《现代教育技术》教学中的实验研究

在《现代教育技术》的课程教学中,笔者对B-learning进行了前测——后测菲对等控制组设计的准实验研究。通过对实验数据的分析发现,在学科知识测验方两,两组无显著差异;在是否完成自己预期目标：疗面,两者呈现了显著差异;在协作方面,两种教学方法也擘现出了较显著的差异。另外,B-learning对于培养学习者认知能力和解决问题的能力非常有效。为了能更好地开展B-learning,教师要帮助学生变革他们的学习观,给学生及时有效地指导,并提供丰富的支持环境。     

Adaptive sliding mode control of modular self-reconfigurable spacecraft with time-delay estimation

The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.     

基于语言评价与模糊数的群体意见共识方法

针对具有自然语言评价信息的群决策问题,给出了一种基于语言评价信息与梯形模糊数的群体意见共识方法.该方法先通过无量纲化处理、语言评价信息转换为梯形模糊数、对梯形模糊数进行集结等步骤,形成群体对方案的综合评价值(梯形模糊数);然后对群体意见进行共识分析和评价;最后对共识结果进行方案排序.通过对实例进行分析,表明该方法能得到切合实际的决策效果.     

基于频率补偿的时延估计方法

由于2个测量站的通道幅相不一致而导致送给时延估计器的两路信号的频率有差异,继而影响时延估计和系统定位精度。首先理论推导了频率差异是如何影响广义相关时延估计的,接着应用频域相关函数对频率差异做准确估计和补偿,最后给出了频差补偿后的时延估计方法。以4种常用通信信号为例,仿真验证了不同信噪比下所提出方法的正确性和有效性。     

具有leakage时滞与传输时滞的神经网络的分支

研究一类具有leakage时滞与传输时滞的两神经元神经网络的分支,分别以leakage时滞和传输时滞为分支参数,通过对模型对应的特征方程进行分析,得到出现Hopf分支的临界性条件,并通过数值例子验证该理论结果.     

Multiproduct batching and scheduling with buffered rework: The case of a car paint shop

We study a problem of scheduling products on the same facility, which is motivated by a car paint shop. Items of the same product are identical. Operations on the items are performed sequentially in batches, where each batch is a set of operations on the same product. Some of the produced items are of the required good quality and some items can be defective. Defectiveness of an item is determined by a given simulated function of its product, its preceding product, and the position of its operation in the batch. Defective items are kept in a buffer of a limited capacity, and they are then remanufactured at the same facility. A minimum waiting time exists for any defective item before its remanufacturing can commence. Each product has a sequence independent setup time which precedes its first operation or its operation following an operation of another product. A due date is given for each product such that all items of the same product have the same due date and the objective is to find a schedule which minimizes maximum lateness of product completion times with respect to their due dates. The problem is proved NP‐hard in the strong sense, and a heuristic Group Technology (GT) solution approach is suggested and analyzed. The results justify application of the GT approach to scheduling real car paint shops with buffered rework. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 458–471, 2014     

基于系统动力学的炮兵群作战体系仿真模型

运用系统动力学方法对炮兵群作战体系的对抗过程建立了仿真模型,分析了不同攻击策略产生的效果,为提高炮兵群作战体系的效能提供了决策依据。     

基于群决策协同网络信息的掩护机编队选择

针对任务机群中掩护机编队的选择,用群决策协同网络信息模型进行了掩护机编队的选择。首先,给出了协同网络、模糊数和语言变量的相关概念;其次,分析了掩护机编队选择的指标体系框架和协同网络信息框架;然后,构建了群决策协同网络信息的数学模型,在此基础上,给出了方案选择的步骤;最后,运用该模型对掩护机编队的选择进行求解。结果表明：该模型能够综合群体专家的知识,解决掩护机编队选择中的定性判断问题。该模型可用于个体指标和协同指标均为定性指标时的方案优选问题。     

具有时滞的比率型Chemostat模型的全局稳定性

研究一类具有时滞的比率型功能性反应的Chemostat模型。研究了模型的边界平衡点和正平衡点的局部稳定性以及Hopf分支的存在性;利用比较定理证明了边界平衡点的全局稳定性;通过构造Liapunov泛函给出了保证系统正平衡点全局稳定的充分条件;并通过数值模拟验证了理论结果。     

Optimal policies for stochastic clearing systems with time-dependent delay penalties

We study stochastic clearing systems with a discrete-time Markovian input process, and an output mechanism that intermittently and instantaneously clears the system partially or completely. The decision to clear the system depends on both quantities and delays of outstanding inputs. Clearing the system incurs a fixed cost, and outstanding inputs are charged a delay penalty, which is a general increasing function of the quantities and delays of individual inputs. By recording the quantities and delays of outstanding inputs in a sequence, we model the clearing system as a tree-structured Markov decision process over both a finite and infinite horizon. We show that the optimal clearing policies, under realistic conditions, are of the on-off type or the threshold type. Based on the characterization of the optimal policies, we develop efficient algorithms to compute parameters of the optimal policies for such complex clearing systems for the first time. We conduct a numerical analysis on the impact of the nonlinear delay penalty cost function, the comparison of the optimal policy and the classical hybrid policy (ie, quantity and age thresholds), and the impact of the state of the input process. Our experiments demonstrate that (a) the classical linear approximation of the cost function can lead to significant performance differences; (b) the classical hybrid policy may perform poorly (as compared to the optimal policies); and (c) the consideration of the state of the input process makes significant improvement in system performance.