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A Comparison of Cross-Entropy and Variance Minimization Strategies
variance minimization cross-entropy importance sampling rareevent simulation likelihood ratio degeneracy
2015/7/6
The variance minimization (VM) and cross-entropy (CE) methods are two versatile adaptive importance sampling procedures that have been successfully applied to a wide variety of difficult rare-event es...
Limit Theorems for Simulation-based Optimization via
Simulation Theory Model Development: Methodologies Types of Simulation
2015/7/6
This paper develops fundamental theory related to the use of simulation-based non-adaptive random search as a means of optimizing a function that can be expressed as an expectation. Our results establ...
Computing Bayesian Means Using Simulation
Bayesian simulation nested simulation independent sampling
2015/7/6
This paper is concerned with the estimation of alpha = Er(Z), where Z is a random vector and the function values r(z) must be evaluated using simulation. Estimation problems of this form arise in the ...
CG VERSUS MINRES: AN EMPIRICAL COMPARISON
conjugate gradient method minimum residual method
2015/7/3
For iterative solution of symmetric systems Ax = b, the conjugate gradient method
(CG) is commonly used when A is positive de nite, while the minimum residual method (MINRES)
is typically reserved f...
A variational principle for computing nonequilibrium fluxes and potentials in genome-scale biochemical networks
Constraint-based modeling Flux balance analysis
2015/7/3
We derive a convex optimization problem on a steady-state nonequilibrium network of biochemical
reactions, with the property that energy conservation and the second law of thermodynamics both hold
a...
Laplace Inversion of Low-Resolution NMR Relaxometry Data Using Sparse Representation Methods
low-resolution NMR sparse reconstruction
2015/7/3
Low-resolution nuclear magnetic resonance (LR-NMR) relaxometry is a
powerful tool that can be harnessed for characterizing constituents in complex materials.
LSQR uses the Golub-Kahan bidiagonalization process to solve sparse least-squares
problems with and without regularization. In some cases, projections of the right-hand
side vector are required, r...
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
large-scale optimization nonlinear programming
2015/7/3
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective
and constraints.Here w...
Autonomy and Common Ground in Human-Robot Interaction: A Field Study
Study Human-Robot Interaction
2015/7/3
The use of robots, especially autonomous mobile robots, to support work is expected
to increase over the next few decades.1However, little empirical research examines
how users form mental models of...
Professor Peter Glynn,Department of Management Science and Engineering at Stanford University（图）
Department of Management Science and Engineering at Stanford University Professor statistics simulation
2015/7/2
Peter W. Glynn is the current Chair of the Department of Management Science and Engineering at Stanford University. He received his Ph.D in Operations Research from Stanford University in 1982. He the...
2015年5月22日至24日，由中国高等教育学会实验室管理工作分会主办的“全国高校虚拟仿真实验教学中心（文理类）建设与发展研讨会”在吉林长春成功举办。本次会议吸引了百余所高校近300名教师参加。中国高等教育学会实验室管理工作分会副理事长兼秘书长、清华大学实验室与设备处处长武晓峰和中国高等教育学会实验室管理工作分会教育培训部副主任，中国地质大学（北京）实验室与资产管理处处长王杰分别主持了研讨会。
基于CAS仿真的组织互动创新机制研究
复杂适应系统 基于CAS理论的领导行为 多主体建模
2014/10/16
现有领导-创新文献没能很好地揭示组织中创新涌现的内在动力机制. 本文提出在既定规则约束下员工（或团队）之间的充分互动是组织创新涌现的内在动力来源，据此领导者可通过调整互动规则和改善互动环境来间接影响知识型员工间的互动行为，从而提升组织的创新绩效，表现为组织作为一个整体能够不断创新自身的现有行为模式，从而动态地适应复杂多变的外部环境. 通过采用多主体建模的计算机仿真方法，验证了“基于CAS理论的领导...
基于排队长度均衡的交叉口信号配时优化策略
排队长度均衡 近似动态规划 信号配时
2014/10/11
城市交通的快速发展和交通需求的不断增长, 使得城市交通拥堵日益严重, 由此造成的时间延误和经济损失越来越大. 鉴于此, 提出了基于排队长度均衡的交叉口信号配时优化策略, 根据排队长度均衡的控制思想, 实时动态调整各相位绿灯时间, 以达到排队长度均衡的控制目标, 保证了绿灯时间的充分利用. 通过近似动态规划方法的引入, 使得该算法具有自学习和自适应的特性, 不依赖于交通流模型. 仿真结果验证了算法的...
基于SVD 的改进抗差UKF 算法及在组合导航中的应用
无迹卡尔曼滤波 改进抗差策略 奇异值分解
2014/10/11
针对GPS/INS 组合导航中因观测异常导致系统状态先验信息矩阵失去对称正定性, 及传统等价权函数抗差算法易遇到病态矩阵, 引起滤波性能下降的问题, 提出一种基于奇异值分解的改进抗差UKF 算法. 该算法克服了先验协方差矩阵负定性变化, 通过判断矩阵病态性实现智能选取抗差策略. 最后利用车载实测数据进行验证, 所得结果表明, SVD-UKF 导航解精度稍优于EKF 算法, 改进的抗差策略能够极大减...