The Determination of AGV’s Traffic Control Model by ID3 through an Implicit Knowledge Learning

1995 ◽  
pp. 679-688
Author(s):  
Dan Jin ◽  
Wenwei Yu ◽  
Yukinori Kakazu
Keyword(s):  
Traffic Control ◽  
Implicit Knowledge ◽  
Control Model ◽  
Knowledge Learning

Translating the Air Traffic Control Model

2017 ◽  
pp. 39-57
Author(s):  
Leon Starr ◽  
Andrew Mangogna ◽  
Stephen Mellor
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Control Model ◽  
Air Traffic

scholarly journals Research on an intelligent traffic congestion control model

2021 ◽  
Vol 336 ◽  
pp. 07001
Author(s):  
Bo Xu ◽  
Jianbing Chen ◽  
Wei Tang
Keyword(s):  
Congestion Control ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Control Model ◽  
Status Quo ◽  
Key Technology ◽  
Related Research ◽  
The Status ◽  
Traffic Congestion Control

This paper summarizes the status quo of intelligent traffic congestion control and vehicle following on traffic road, puts forward the key technology model and its content of intelligent traffic control, elaborates the model and content in detail, and summarizes the research done, hoping to provide reference for the related research on intelligent traffic congestion control.

scholarly journals Development of a methodology to backcalculate pavement layer moduli using the traffic speed deflectometer

2018 ◽  
Vol 45 (5) ◽  
pp. 377-385 ◽  
Author(s):  
Omar Elbagalati ◽  
Momen Mousa ◽  
Mostafa A. Elseifi ◽  
Kevin Gaspard ◽  
Zhongjie Zhang
Keyword(s):  
Traffic Control ◽  
Coefficient Of Determination ◽  
Falling Weight Deflectometer ◽  
Ann Model ◽  
Acceptable Accuracy ◽  
Traffic Speed ◽  
Artificial Neural Network Ann ◽  
Falling Weight ◽  
Good Agreement

Backcalculation analysis of pavement layer moduli is typically conducted based on falling weight deflectometer (FWD) measurements; however, the stationary nature of FWD requires lane closure and traffic control. To overcome these limitations, a number of continuous deflection devices were introduced in recent years. The objective of this study was to develop a methodology to incorporate traffic speed deflectometer (TSD) measurements in the backcalculation analysis. To achieve this objective, TSD and FWD measurements were used to train and to validate an artificial neural network (ANN) model that would convert TSD deflection measurements to FWD deflection measurements. The ANN model showed acceptable accuracy with a coefficient of determination of 0.81 and a good agreement between the backcalculated moduli from FWD and TSD measurements. Evaluation of the model showed that the backcalculated layer moduli from TSD could be used in pavement analysis and in structural health monitoring with a reasonable level of accuracy.

Issues with data protection as command and control regulation

2020 ◽  
pp. 87-108
Author(s):  
Raphaël Gellert
Keyword(s):  
Data Protection ◽  
Command And Control ◽  
Control Model ◽  
Reform Process ◽  
Control Regulation ◽  
And Control

Chapter 3 shows that a number of the issues that data protection has encountered and which have served as the impetus for the GDPR reform process can be understood from the regulatory viewpoint. More in particular, they amount to the traditional criticism addressed against command and control rulemaking. It is possible to argue that the command and control model of regulation is based upon two assumptions. First, enforcement is operated through sanctions or the threat thereof—what is referred to as deterrencedeterrence|, and it is assumed that such deterrence always works. Second, it is assumed that the regulatory goalsregulatory goals| (and the standards and safeguards they lead to) are somewhat unproblematic. This last set of issues is multi-dimensional insofar as it affects the determination of what counts as an adequate standard and safeguard, but it also affects the implementation in practice of these standards. Just as determining what is the behaviour that will lead to the achievement of regulators is less than obvious, so is the concrete implementation and compliance with the various rules that are meant to lead to such behaviour. This is encapsulated for instance in the data controllers’ uncertainty on how exactly to apply certain data protection provisions, or in the inefficiency of a number of mechanisms such as notification obligations. Finally, due notice should be paid to technological evolutions, which can aggravate these issues.

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