Automatic model classification of measured Internet traffic

2003 ◽  
Author(s):  
Yi Zeng ◽  
T.M. Chen
Keyword(s):  
Internet Traffic ◽  
Model Classification

scholarly journals Machine learning: Enhancing the Perception of the Computer

2020 ◽  
Vol 9 (4) ◽  
pp. 758-761
Keyword(s):  
Machine Learning ◽  
Computer Training ◽  
Internet Traffic ◽  
The Internet ◽  
Popular Method ◽  
Exponential Increase ◽  
Computer Teaching ◽  
Traffic Detection ◽  
The Web

The advancement of technology and networking allows the use of the Web incredibly important. There is thus an exponential increase in data and information via the Internet. This flow thus is a beneficial field of study which can be defined accurately. Internet traffic detection is a very popular method of identifying information. Although so many methods have been successfully developed for classifying internet traffic, computer training technology among them is most popular. A short study of the classification of Internet traffic on various managed and non-regulated computer teaching systems was undertaken by many researchers. This paper will give various ideas to the other researcher’s and help them to learn a lot about machine learning

scholarly journals Towards a Validation Methodology for Macroeconomic Agent-Based Models

2021 ◽  
Author(s):  
Sebastiaan Tieleman
Keyword(s):  
Emergent Properties ◽  
Agent Based Models ◽  
Important Distinction ◽  
Agent Based ◽  
Model Classification ◽  
Classification Framework ◽  
The Difference ◽  
To Come

AbstractAgent-based models provide a promising new tool in macroeconomic research. Questions have been raised, however, regarding the validity of such models. A methodology of macroeconomic agent-based model (MABM) validation, that provides a deeper understanding of validation practices, is required. This paper takes steps towards such a methodology by connecting three elements. First, is a foundation of model validation in general. Second is a classification of models dependent on how the model is validated. An important distinction in this classification is the difference between mechanism and target validation. Third, is a framework that revolves around the relationship between the structure of models of complex systems with emergent properties and validation in practice. Important in this framework is to consider MABMs as modelling multiple non-trivial levels. Connecting these three elements provides us with a methodology of the validation of MABMs and allows us to come to the following conclusions regarding MABM validation. First, in MABMs, mechanisms at a lower level are distinct from, but provide input to higher levels of mechanisms. Since mechanisms at different levels are validated in different ways we can come to a specific characterization of MABMs within the model classification framework. Second, because the mechanisms of MABMs are validated in a direct way at the level of the agent, MABMs can be seen as a move towards a more realist approach to modelling compared to DSGE.

Model Classification of Guided Wave Signal based on the Visibility Graph and SVM

2018 ◽  
Author(s):  
Weilei MU ◽  
Zhengxing ZOU ◽  
Hailiang SUN ◽  
Guijie LIU ◽  
Guangyin XIA ◽  
...  
Keyword(s):  
Guided Wave ◽  
Visibility Graph ◽  
Wave Signal ◽  
Model Classification

scholarly journals Model Classification Of Nominal Value And The Original Of IDR Money By Applying Evolutionary Neural Network

2020 ◽  
Vol 3 (2) ◽  
pp. 258-265
Author(s):  
Al-Khowarizmi Al-Khowarizmi
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Genetic Algorithms ◽  
Object Recognition ◽  
Success Rate ◽  
Model Classification ◽  
Evolutionary Neural Network ◽  
Evolutionary Neural Networks

Indonesian Rupiah (IDR) banknotes have unique characteristics that distinguish them from one another, both in the form of numbers, zeros and background images. This pattern of each type of banknote will be modeled in order to test the nominal value and authenticity of IDR, so as to be able to distinguish not only IDR banknotes but also other denominations. Evolutionary Neural Network is the development of the concept of evolution to get a neural network (NN) using genetic algorithms (GA). In this paper the application of evolutionary neural networks with less input is able to have a better success rate in object recognition, because the parameters for producing neural networks are far better

scholarly journals Financial aspects of transport infrastructure development in regions

2018 ◽  
Vol 216 ◽  
pp. 02002
Author(s):  
Vyacheslav Bubnov ◽  
Yulia Bubnova
Keyword(s):  
Economic Growth ◽  
Factor Model ◽  
Transport Infrastructure ◽  
Infrastructure Development ◽  
Railway Transport ◽  
Model Classification ◽  
Regional Market ◽  
Level Of Economic Development ◽  
Selection Of

The level of economic development depends on many factors, among which infrastructure, including railway transport, is the key one. Financing of infrastructure-related projects on the regional level encourages economic growth. However, different level of overall development of subject of the Russian Federation causes inequality in the level of transport infrastructure development and makes common approach to its financing inapplicable. The necessity appears to build a model of financing for transport-related infrastructure with the use of statistical data and mathematical approach with the account of regional market peculiarities. Due to selection of indicators affecting economic growth and building parametric factor model, classification of financing on subfederal level was carried out, which makes it applicable for states with federal structure.

Sequential Message Characterization for Early Classification of Encrypted Internet Traffic

2021 ◽  
pp. 1-1
Author(s):  
Wenxiong Chen ◽  
Feng Lyu ◽  
Fan Wu ◽  
Peng Yang ◽  
Guangtao Xue ◽  
...  
Keyword(s):  
Internet Traffic ◽  
Early Classification
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