Optimal feedback structure and interactional pattern in formative peer practices: Students' beliefs

System ◽  
2018 ◽  
Vol 74 ◽  
pp. 9-20 ◽  
Author(s):  
Shima Ghahari ◽  
Marzie Sedaghat
2020 ◽  
Vol 4 ◽  
pp. 96-109
Author(s):  
A.V. Romanov ◽  
◽  
M.V. Yachmenova ◽  

Based on the example of flood warning data provided by EFAS for the territory of Northwestern Administration for Hydrometeorology and Environmental Monitoring in 2018-2020, the structure of the systematized issues of the EFAS portal is analyzed. The issues determine a feedback for the year-round monitoring of the accuracy of flood forecasting using the LISFLOOD base model, as well as its calibration. Several most important feedback sections are highlighted, that allow improving significantly a procedure for the quantitative and qualitative differentiated assessment of short- and medium-range flood forecasts. Using the results of the numerical analysis, a general description of the EFAS flood warning system quality and the prospects for the participation of the Russian Federation in it are given. Keywords: flooding, hydrological forecasts, forecast lead time, feedback, forecast accuracy


Author(s):  
Jongeun Choi ◽  
Dejan Milutinović

This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.


2020 ◽  
Vol 53 (2) ◽  
pp. 12638-12643
Author(s):  
Michael Sinner ◽  
Vlaho Petrović ◽  
Frederik Berger ◽  
Lars Neuhaus ◽  
Martin Kühn ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3083
Author(s):  
Mohamed Amine Fnaiech ◽  
Jaroslaw Guzinski ◽  
Mohamed Trabelsi ◽  
Abdellah Kouzou ◽  
Mohamed Benbouzid ◽  
...  

This paper presents a newly designed switching linear feedback structure of sliding mode control (SLF-SMC) plugged with an model reference adaptive system (MRAS) based sensorless field-oriented control (SFOC) for induction motor (IM). Indeed, the performance of the MRAS depends mainly on the operating point and the parametric variation of the IM. Hence, the sliding mode control (SMC) could be considered a good control alternative due to its easy implementation and robustness. Simulation and experimentation results are presented to show the superiority of the proposed SLF-SMC technique in comparison with the classical PI controller under different speed ranges and inertia conditions.


Author(s):  
Jinghai Shao ◽  
Sovan Mitra ◽  
Andreas Karathanasopoulos

AbstractIn this paper we provide a stock price model that explicitly incorporates credit risk, under a stochastic optimal control system. The stock price model also incorporates the managerial control of credit risk through a control policy in the stochastic system. We provide explicit conditions on the existence of optimal feedback controls for the stock price model with credit risk. We prove the continuity of the value function, and then prove the dynamic programming principle for our system. Finally, we prove the Viscosity Solution of the Hamilton–Jacobi–Bellman equation. This paper is particularly relevant to industry, as the impact of credit risk upon stock prices has been prominent since the commencement of the Global Financial Crisis.


Sign in / Sign up

Export Citation Format

Share Document