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Mauro Fazion Filho
The nonlinear dynamical behaviour of a network that is submitted to disturbances is the starting point of this work, where we consider a low voltage line (the network) with nonlinear varistor filters responding, dynamically, to those disturbances. Networ...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Haiyan Gao, Zhichao Chen and Weiqiang Tang
The method proposed can be used for the identification and control of multivariable nonlinear systems.
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Benjamin Plaster and Gautam Kumar
Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions have been of interest to engineers, mathematicians and physicists over the last several decades. With the motivation of developing com...
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Ebenezer O. Oluwasakin and Abdul Q. M. Khaliq
Artificial neural networks have changed many fields by giving scientists a strong way to model complex phenomena. They are also becoming increasingly useful for solving various difficult scientific problems. Still, people keep trying to find faster and m...
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Nikolaos I. Xiros and Erdem Aktosun
The hydrodynamic forces on an oscillating circular cylinder are predicted using neural networks under flow conditions where Vortex-Induced Vibrations (VIV) are known to occur. The derived neural network approximators are then incorporated in a dynamical ...
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Fan Wang, Gaogao Dong and Lixin Tian
In real systems, some damaged nodes can spontaneously become active again when recovered from themselves or their active neighbours. However, the spontaneous dynamical recovery of complex networks that suffer a local failure has not yet been taken into c...
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Franco Bagnoli, Emanuele Bellini, Emanuele Massaro and Raúl Rechtman
Percolation, in its most general interpretation, refers to the ?flow? of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction?diffusion...
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Jorge A. Laval, Ludovic Leclercq, Nicolas Chiabaut
Pág. 517 - 530
This paper investigates the dynamic user equilibrium (DUE) on a single origin-destination pair with two alternative routes, a freeway with a fixed capacity and the surrounding city-streets network, modeled with a network macroscopic fundamental diagram (...
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Micha Ober, Stefan Katzenbeisser and Kay Hamacher
The Bitcoin network of decentralized payment transactions has attracted a lot of attention from both Internet users and researchers in recent years. Bitcoin utilizes a peer-to-peer network to issue anonymous payment transactions between different users. ...
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Claudio Meneguzzer
Understanding the many facets of repeated route choice behavior in traffic networks is essential for obtaining accurate flow forecasts and enhancing the effectiveness of traffic management measures. This paper presents a model of the day-to-day evolution...
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Angel Giménez, Miguel A. Murcia, José M. Amigó, Oscar Martínez-Bonastre and José Valero
In recent years, Active Queue Management (AQM) mechanisms to improve the performance of TCP/IP networks have acquired a relevant role. In this paper, we present a simple and robust RED-type algorithm together with a couple of dynamical variants with the ...
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Franco Bagnoli, Guido de Bonfioli Cavalcabo?, Banedetto Casu and Andrea Guazzini
We investigate the problem of the formation of communities of users that selectively exchange messages among them in a simulated environment. This closed community can be seen as the prototype of the bubble effect, i.e., the isolation of individuals from...
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Quintino Francesco Lotito, Davide Zanella and Paolo Casari
The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fa...
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T. M. Mishchenko
Pág. 121 - 126
Introduction: By means of the mathematical or computer (imitating) modeling the emergency, especially stochastic, transient electromagnetic and / or electro energetic processes in the electric traction system of the alternating current should be investig...
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Liudmila Chizhikova
Pág. 109 - 114
The complexity of the control systems, integration of subsystems and interfaces, software development of control systems evoke the special task of the optimal operation mode search with given limitations in time of data operation, data exchan...
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Gianluca d?Addese, Salvatore Magrì, Roberto Serra and Marco Villani
The properties of most systems composed of many interacting elements are neither determined by the topology of the interaction network alone, nor by the dynamical laws in isolation. Rather, they are the outcome of the interplay between topology and dynam...
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Stefan Klus and Patrick Gelß
Interest in machine learning with tensor networks has been growing rapidly in recent years. We show that tensor-based methods developed for learning the governing equations of dynamical systems from data can, in the same way, be used for supervised learn...
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Michael Schultz and Stefan Reitmann
In this paper we address the prediction of aircraft boarding using a machine learning approach. Reliable process predictions of aircraft turnaround are an important element to further increase the punctuality of airline operations. In this context, aircr...
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Michael Schultz and Stefan Reitmann
In this paper we address the prediction of aircraft boarding using a machine learning approach. Reliable process predictions of aircraft turnaround are an important element to further increase the punctuality of airline operations. In this context, aircr...
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