搜索结果: 1-15 共查到“工学 Stochastic”相关记录78条 . 查询时间(0.165 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
通信压缩 分布式 随机优化 下界 加速算法
2023/11/29
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Stochastic Navier-Stokes equations via convex integration
凸积分 随机 纳维-斯托克斯方程
2023/5/8
梯度增强的Stochastic Co-Kriging模型建模及其在CFD非嵌入式不确定性量化中应用的研究进展(图)
梯度增强 Stochastic Co-Kriging 模型建模 CFD 非嵌入式 不确定性
2019/10/30
作为一项极其复杂的系统工程,飞行器的研制总会受到制造误差、飞行状态等诸多不确定性因素的影响,如果这些不确定性因素在设计过程中被忽视,很可能会导致飞行器整体性能急剧变差,甚至造成致命性的灾难。因此,近年来飞行器的不确定性研究方法和手段在航空航天领域得到了广泛应用,NASA早在2002年就开始着手规划考虑不确定性因素影响的研究工作,AIAA和ASME每年都举办关于不确定性研究的专题研讨会。当前我国各型...
梯度增强的Stochastic Co-Kriging模型建模及其在CFD非嵌入式不确定性量化中应用的研究进展(图)
梯度增强 Stochastic Co-Kriging 模型建模 CFD非嵌入式 不确定性量化
2019/10/16
作为一项极其复杂的系统工程,飞行器的研制总会受到制造误差、飞行状态等诸多不确定性因素的影响,如果这些不确定性因素在设计过程中被忽视,很可能会导致飞行器整体性能急剧变差,甚至造成致命性的灾难。因此,近年来飞行器的不确定性研究方法和手段在航空航天领域得到了广泛应用,NASA早在2002年就开始着手规划考虑不确定性因素影响的研究工作,AIAA和ASME每年都举办关于不确定性研究的专题研讨会。当前我国各型...
中国地质大学科学技术发展院宗小峰自动化学院 Automatica, Available online 20 March 2018, Stability of stochastic functional differential systems using degenerate Lyapunov functionals and applications
随机;系统;稳定性;方面新成果
2021/10/21
2018年3月20日,控制领域国际顶级期刊《Automatica》刊发了中国地质大学自动化学院宗小峰教授的“随机系统稳定性方面新成果”--Stability of stochastic functional differential systems using degenerate Lyapunov functionals and applications。
STOCHASTIC SURFACE MESH RECONSTRUCTION
TLS point cloud point error model error ellipsoid variance-covariance propagation surface triangulation
2018/6/4
A generic and practical methodology is presented for 3D surface mesh reconstruction from the terrestrial laser scanner (TLS) derived point clouds. It has two main steps. The first step deals with deve...
IUTAM Symposium on Stochastic dynamical systems approaches to fluid flow transitions
IUTAM Seminar Stochastic dynamic system A fluid transition methods
2017/12/13
IUTAM Symposium on Stochastic dynamical systems approaches to fluid flow transitions.
STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL
Stochastic Coloured Petri net Critical Infrastructure Interdependency Disaster Preparedness Modelling and Simulation Healthcare Critical Infrastructure
2016/11/30
The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in re...
Stochastic Superoptimization
64-bit x86 x86-64 Binary Markov Chain Monte Carlo MCMC Stochastic Search Superoptimization SMT
2016/5/24
We formulate the loop-free binary superoptimization task as a stochastic search problem. The competing constraints of transformation correctness and performance improvement are encoded as terms in a c...
Stochastic Optimization of Floating Point Programs with Tunable Precision
64-bit x86 x86-64, Binary Markov Chain Monte Carlo MCMC Stochastic Search SMT Floating-Point Precision
2016/5/24
The aggressive optimization of floating-point computations is an important problem in high-performance computing. Unfortunately,floating-point instruction sets have complicated semantics that often fo...
The optimization of short sequences of loop-free, fixed-point assembly code sequences is an important problem in highperformance computing. However, the competing constraints of transformation correct...
Stochastic Combinatorial Optimization via Poisson Approximation
Stochastic Knapsack Stochastic Bin Packing Expected Util- ity Maximization
2016/1/23
We study several stochastic combinatorial problems, includ-ing the expected utility maximization problem, the stochas-tic knapsack problem and the stochastic bin packing prob-lem. A common technical c...
The Power of Online Learning in Stochastic Network Optimization
Power Online Learning Stochastic Network Optimization
2016/1/22
In this paper, we investigate the power of online learning in stochastic network optimization with unknown system statistics a priori. We are interested in understanding how information and learning c...
Approximating the Expected Values for Combinatorial Optimization Problems over Stochastic Points
Approximating Expected Values Combinatorial Optimization Problems Stochastic Points
2016/1/22
We consider the stochastic geometry model where the location of each node is a random point in a given metric space,or the existence of each node is uncertain. We study the problem-s of computing the ...
Receding Learning-aided Control in Stochastic Networks
Receding learning-aided control Detection Network optimization Queueing
2016/1/22
In this paper, we develop the Receding Learning-aided Control algorithm ( RLC ) for solving optimization problems in general stochastic networks with potentially non-stationary system dynamics. RLC is...