System Prediction and Control Model Based on Data Simulation and its Application

2010 ◽  
Author(s):  
Yi-sheng Hu ◽  
Chao Min ◽  
Zhi-bin Liu
Keyword(s):  
Control Model ◽  
Data Simulation ◽  
Model Based ◽  
Prediction And Control ◽  
And Control

scholarly journals A model based study on the dynamics of COVID-19: Prediction and control

2020 ◽  
Vol 136 ◽  
pp. 109889 ◽  
Author(s):  
Manotosh Mandal ◽  
Soovoojeet Jana ◽  
Swapan Kumar Nandi ◽  
Anupam Khatua ◽  
Sayani Adak ◽  
...  
Keyword(s):  
Model Based ◽  
Prediction And Control ◽  
And Control

scholarly journals Furnace heat prediction and control model and its application to large blast furnace

2019 ◽  
Vol 38 (2019) ◽  
pp. 884-891
Author(s):  
Zhuang-nian Li ◽  
Man-sheng Chu ◽  
Zheng-gen Liu ◽  
Gen-ji Ruan ◽  
Bao-feng Li
Keyword(s):  
Blast Furnace ◽  
Control Model ◽  
Heat Index ◽  
Model Parameters ◽  
Stable Operation ◽  
Oxygen Balance ◽  
Large Blast ◽  
Large Blast Furnace ◽  
Prediction And Control ◽  
And Control

AbstractBlast furnace heat is the key to the blast furnace’s high efficiency and stable operation, and it is difficult to maintain a suitable temperature for large blast furnace operations. When designing the furnace heat prediction and control model, parameters with good reliability and measurability should be chosen to avoid using less accurate parameters and to ensure the accuracy and practicability of the model. This paper presents an effective model for large blast furnace temperature prediction and control. Using thermal equilibrium and the carbon-oxygen balance of the blast furnace’s high-temperature zone, the slag-iron heat index was calculated. Using the relation between the molten iron temperature and slag-iron heat index, the furnace heat parameter can be calculated while production conditions are changed,which can guide furnace heat control.

scholarly journals The algorithmic anatomy of model-based evaluation

2014 ◽  
Vol 369 (1655) ◽  
pp. 20130478 ◽  
Author(s):  
Nathaniel D. Daw ◽  
Peter Dayan
Keyword(s):  
Twentieth Century ◽  
Reinforcement Learning ◽  
Evaluation Methods ◽  
Neural Data ◽  
Model Based ◽  
Model Free ◽  
Prediction And Control ◽  
And Control

Despite many debates in the first half of the twentieth century, it is now largely a truism that humans and other animals build models of their environments and use them for prediction and control. However, model-based (MB) reasoning presents severe computational challenges. Alternative, computationally simpler, model-free (MF) schemes have been suggested in the reinforcement learning literature, and have afforded influential accounts of behavioural and neural data. Here, we study the realization of MB calculations, and the ways that this might be woven together with MF values and evaluation methods. There are as yet mostly only hints in the literature as to the resulting tapestry, so we offer more preview than review.

Prediction and control model of shale induced fracture leakage pressure

2021 ◽  
Vol 198 ◽  
pp. 108186
Author(s):  
Xiaopeng Zhai ◽  
Hui Chen ◽  
Yishan Lou ◽  
Huimei Wu
Keyword(s):  
Control Model ◽  
Prediction And Control ◽  
And Control
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