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Batch size effects on the efficiency of control variates in simulation
1989
European Journal of Operational Research
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This paper considers the combined use of control variates and batching for estimating the steady-state mean of an infinite-horizon process via simulation. ...
Properties of the point and interval estimators from such a procedure are derived as functions of the number of batches and the number of control variates when the total sample size is fixed. ...
Neuhardt of The Ohio State University, Bruce Schmeiser, and James R. Wilson of Purdue University, and comments by two anonymous referees, one of whom suggested the alternate expression for Result 3. ...
doi:10.1016/0377-2217(89)90212-9
fatcat:wwtb7rh6trfpra5rq4nnqyvqcu
Optimization via simulation: A review
1994
Annals of Operations Research
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We review techniques for optimizing stochastic discrete-event systems via simulation. ...
In practice, the pooled variance could be used to estimate the additional number of replications needed to make a final determination. where J i and s have the same meaning as in the MCA procedure. ...
In particular, the independence assumption would rule out the implementation of powerful variance reduction techniques such as common random numbers and control variates. ...
doi:10.1007/bf02136830
fatcat:srcum3kqvzh33gbd4g3kghncje
Lidar-assisted model predictive control of wind turbine fatigue via online rainflow counting considering stress history
2022
Wind Energy Science
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The formulation is tested in realistic simulation scenarios in which the states are estimated by a moving horizon estimator and the wind is predicted by a lidar simulator. ...
The tuning procedure for the controller toolchain is carefully explained. ...
The authors would like to thank the company sowento GmbH for kindly providing a free license of their lidar simulator. ...
doi:10.5194/wes-7-1605-2022
fatcat:h5azjwl74fhhrahq6xio5m4s5a
Automated Verification and Synthesis of Stochastic Hybrid Systems: A Survey
[article]
2022
arXiv
pre-print
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Automated verification and policy synthesis for stochastic hybrid systems can be inherently challenging: this is due to the heterogeneity of their dynamics (presence of continuous and discrete components ...
In this survey, we overview the most recent results in the literature and discuss different approaches, including (in)finite abstractions, verification and synthesis for temporal logic specifications, ...
We hope that this survey article provides an introduction to the foundations of SHS, towards an easier understanding of many challenges and existing solutions related to formal verification and control ...
arXiv:2101.07491v2
fatcat:dpir554ebfclhpj5m7e7fi2hv4
A Deep Reinforcement Learning Framework for Eco-driving in Connected and Automated Hybrid Electric Vehicles
[article]
2021
arXiv
pre-print
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An Eco-driving simulation environment is developed for training and evaluation purposes. ...
Connected and Automated Vehicles (CAVs), in particular those with multiple power sources, have the potential to significantly reduce fuel consumption and travel time in real-world driving conditions. ...
ACKNOWLEDGMENT The authors acknowledge the support from the United States Department of Energy, Advanced Research Projects Agency -Energy (ARPA-E) NEXTCAR project (Award Number DE-AR0000794) and The Ohio ...
arXiv:2101.05372v2
fatcat:euqqbueed5fmpbubqal64tokqa
Deep Bayesian inference for seismic imaging with tasks
[article]
2022
arXiv
pre-print
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For instance, it admits estimates for the pointwise standard deviation on the image and for confidence intervals on its automatically tracked horizons. ...
to uncertainty on the tracked horizons. ...
[53] showed that for infinitely wide CNNs, i.e. ...
arXiv:2110.04825v3
fatcat:bqwegxozabcxxm7r4mfnrbxpxu
A real-time and eco-layout platform for optimization of supply/costs for water distribution systems management
2022
Water Science and Technology : Water Supply
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Operating view is provided through a real-time control scheduler (RTC), which satisfactorily attends to solve the dynamic control problem at every timestep via minimization of energy costs over the day ...
and satisfying hydraulic reliability constraints through suggesting near-optimal pump schedules. ...
For any pump, the daily energy cost referred to the cost for each selected timestep (k) within the control horizon (T). Therefore, the cost for each pump (J p ) achieves via Equation (1). ...
doi:10.2166/ws.2022.258
fatcat:t326gs3kr5berkakkqvnyvz4lm
Stochastic process in railway traffic flow: Models, methods and implications
2021
Transportation Research Part C: Emerging Technologies
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One potential for automation is the reduction of those margins by means of optimized traffic management and train control, for an estimated increase of 30% in the transport capacity. ...
The models can be useful to estimate the benefits introduced by automation in railways, including Automated Train Operation (ATO). 2 aspects (see Wang et al., 2020b for frequency-domain stability analysis ...
Zhou et al. (2017) developed a rolling horizon stochastic optimal control framework for Adaptive Cruise Control and Cooperative Adaptive Cruise Control. ...
doi:10.1016/j.trc.2021.103167
fatcat:nr6b6dsjynefpbipuypw4tkqj4
Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision
2021
PLoS Computational Biology
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errors based on the available limb state estimate. ...
In SFFC, movement timing results from the minimization of the intrinsic factors of effort and variance due to constant and signal-dependent motor noise, and movement variability depends on the integration ...
For instance, [22] determined duration in an infinite-horizon SOC formulation by comparing the magnitude of endpoint variance to the target's width, which allowed to predict the speed-accuracy trade-off ...
doi:10.1371/journal.pcbi.1009047
pmid:34115757
fatcat:6fvsk4nv7facncu2tbdadlq7i4
Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision
2021
figshare.com
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errors based on the available limb state estimate. ...
In SFFC, movement timing results from the minimization of the intrinsic factors of effort and variance due to constant and signal-dependent motor noise, and movement variability depends on the integration ...
For instance, [22] determined duration in an infinite-horizon SOC formulation by comparing the magnitude of endpoint variance to the target's width, which allowed to predict the speed-accuracy trade-off ...
doi:10.6084/m9.figshare.16567626.v1
fatcat:btzxhc7c6ndzjo3x54eoger4uq
Frenet-Based Algorithm for Trajectory Prediction
2004
Journal of Guidance Control and Dynamics
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Unfortunately no such a priori estimate is possible for the process noise variance a, or, equivalently, for the ratio a, /o,. ...
In this case, the white noise variance is 0, = 0.1 deg-s ! and also in this case, the error rms for the estimated signal is less then 4 g,. ...
doi:10.2514/1.9338
fatcat:j5sfv4x3ozh5totvvl53hfa3au
A New Efficient Adaptive Control of Torsional Vibrations Induced by Switched Nonlinear Disturbances
2019
International Journal of Applied Mathematics and Computer Science
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The controller's performance is examined via numerical simulations of the stabilization of the drilling system. ...
This approach allows generating a control law that takes into account the impact of the friction on the system dynamics and optimally steers the system to the desired trajectory. ...
for the result of simulation governed with noise variance g = 200 N 2 m 2 and J1 stands for the trajectory of simulation with the noise variance g = 1 N 2 m 2 ) (a), control values generated by Algorithm ...
doi:10.2478/amcs-2019-0021
fatcat:6tibm4bczvgifb2cldfevklk5i
The role of statistical methodology in simulation
1978
ACM SIGSIM Simulation Digest
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For Monte Carlo simulations some tactical problems are discussed: runlength and variance reduction. ...
In stochastic simulation two tactical problems exist: Variance reduction can be achieved through special techniques such as common random numbers, antithetic variates, control variates (regression sampling ...
If we wish to estimate, say, average waiting time n for a specific average input value y, then we may correct our estimate via the regression model yi -BO t S1 . xi t ui (i-1,... ...
doi:10.1145/1102786.1102793
fatcat:pgyvsk3wxzdw7n5aaxcgvjmdpu
2020 Index IEEE Transactions on Automation Science and Engineering Vol. 17
2020
IEEE Transactions on Automation Science and Engineering
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., +, TASE July 2020 1237-1249
Infinite horizon
Supervisory Model Predictive Control for Optimal Energy Management
of Networked Smart Greenhouses Integrated Microgrid. ...
Yan, J., +, TASE July 2020 1361-1375 Variation Source Identification in Manufacturing Processes Using Bayesian Approach With Sparse Variance Components Prior. ...
Project management Solving the Tree-Structured Task Allocation Problem via Group Multirole Assignment. ...
doi:10.1109/tase.2020.3037603
fatcat:kyt63444lfc45amrjebyjw34qu
Mitigating Bunching with Bus-following Models and Bus-to-Bus Cooperation
2015
2015 IEEE 18th International Conference on Intelligent Transportation Systems
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Then a combined state estimation and remote control scheme, which is based on the Linear-Quadratic Gaussian theory, is developed to capture the effect of bus stops, traffic disturbances, and randomness ...
In this context, we first propose practical linear and nonlinear control laws to regulate space headways and speeds, which would lead to bunching cure. ...
The infinite time horizon in (10) is taken in order to obtain a time-invariant feedback law according to the LQG control theory. ...
doi:10.1109/itsc.2015.18
dblp:conf/itsc/AmpountolasK15
fatcat:phh2mthmrndsfm7c6bund6ftgu
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