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Capturing Dependency Among Link Boundaries in a Stochastic Dynamic Network Loading Model

Carolina Osorio, Gunnar Flötteröd
2015 Transportation Science  
This work adds realistic dependency structure to a previously developed analytical stochastic network loading model.  ...  The previous approach captured dependency between the upstream and downstream boundary conditions within a link (i.e. the respective cumulative flows) only in terms of time-dependent expectations without  ...  Introduction A network loading model describes how a time-dependent travel demand advances through a network.  ... 
doi:10.1287/trsc.2013.0504 fatcat:75wi7bajgfgrvkedlohlohxuqa

Dynamic Constraint-based Influence Framework and its Application in Stochastic Modeling of Load Balancing [article]

Ehsan Siavashi, Mahshid Rahnamay-Naeini
2020 arXiv   pre-print
In this paper, the proposed DCIM is successfully applied to stochastic modeling of load balancing in networks of computing nodes allowing for prediction of the load distribution in the system, which is  ...  constraint-based and dynamic interactions in networks.  ...  nodes to capture these scenarios. 2) IM Lacks the Capability of Capturing Changes in the Internal Dynamics of MCs: In many real world networks, the dynamics of state transitions of a node (modeled by  ... 
arXiv:2006.15182v1 fatcat:d2oy72hufjaj3hifzcvphxrrsm

Analytical Dynamic Traffic Assignment Model with Probabilistic Travel Times and Perceptions

Henry Liu, Xuegang Ban, Bin Ran, Pitu Mirchandani
2002 Transportation Research Record  
This paper aims to advance the state-of-the-art in DTA modeling in the sense that the proposed model captures the travelers' decision making among discrete choices in a probabilistic and uncertain environment  ...  Dynamic traffic assignment (DTA) has been a topic of substantial research during the past decade.  ...  CONCLUDING REMARKS In this paper, we presented an analytical approach to formulate a dynamic traffic assignment model, which capture travelers' route choice behavior in a dynamic and stochastic network  ... 
doi:10.3141/1783-16 fatcat:hbgp4v243feldbk333b6rvjs3e

Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models

Hazhir Rahmandad, John Sterman
2008 Management science  
Whereas DE models assume homogeneity and perfect mixing within compartments, AB models can capture heterogeneity across individuals and in the network of interactions among them.  ...  In some conditions, however, these differences in means are small compared to variability caused by stochastic events, parameter uncertainty, and model boundary.  ...  In a second set of tests, we also examine the ability of the DE model to capture the dynamics of each network structure in the realistic situation where parameters are poorly constrained by biological  ... 
doi:10.1287/mnsc.1070.0787 fatcat:gpltt5zwlnhtff7qbq36wctssq

Dynamic failure rate model of an electric motor comparing the Military Standard and Svenska Kullagerfabriken (SKF) methods

Diego D'Urso, Ferdinando Chiacchio, Dario Borrometi, Antonio Costa, Lucio Compagno
2021 Procedia Computer Science  
While the former predicts more conservative behaviours, the latter, taking into account lubrication conditions, dynamic loads and a better knowledge of materials quality, enables to capture the evolut  ...  While the former predicts more conservative behaviours, the latter, taking into account lubrication conditions, dynamic loads and a better knowledge of materials quality, enables to capture the evolut  ...  Specifically, a variation in the boundary conditions of the system affects the failure/repair behaviour managed by the stochastic model.  ... 
doi:10.1016/j.procs.2021.01.262 fatcat:lemvgdsdhre3nckc4u674ewv54

Towards disaggregate dynamic travel forecasting models

Moshe Ben-Akiva, Bottom Jon, Gao Song, Iaris N. Koutsopoulos, Wen Yang
2007 Tsinghua Science and Technology  
link or from one link to the next along a path.  ...  These are known as dynamic traffic assignment (DTA) models, and research in this area is still very active. Page 8 of 44 choice, among other travel decisions.  ...  Dynamic network loading models typically resolve this mutual dependency either analytically or through simulation.  ... 
doi:10.1016/s1007-0214(07)70019-6 fatcat:k35gliavafetfn5pdrgbhsk55u

Stability Analysis of Biological Network Topologies during Stochastic Simulation

Davide Prandi, Tommaso Mazza
2011 Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques  
Recent advances in the stochastic simulation of biological systems have exploited the weighted dependency di-graph as a compact representation of the computational workload.  ...  We measure the stability of such indices over time and make a case for considering them in parallel stochastic simulation.  ...  In fact, large changes in the propensities of the boundary reactions would cause a forced run-time rearrangement of the groups in order to bring the boundary dependencies down.  ... 
doi:10.4108/icst.simutools.2011.245590 dblp:conf/simutools/MazzaP11 fatcat:42c56nosbndjrjcocqa3v6ukaa

Modelling Dynamic Urban Road Networks Performance under Congestion Pricing Strategies

Loukas Dimitriou, Antony Stathopoulos
2008 IFAC Proceedings Volumes  
In the current study, an evaluation framework of the application of a congestion pricing strategy based on the marginal travel cost is presented, able to identify the dynamic impact of congestion pricing  ...  transportation networks management.  ...  The proposed dynamic system in order to identify multiple user classes and to model their dynamic trip choices, is composed of a network model able to provide traffic conditions (link-path travel times  ... 
doi:10.3182/20080706-5-kr-1001.02211 fatcat:ntkuumlngfatlhumy7kv4dqvpe

Biokinetic Mechanisms Linked With Musculoskeletal Health Disparities: Stochastic Models Applying Tikhonov's Theorem to Biomolecule Homeostasis

Asit K. Saha, Yu Liang, Sean S. Kohles
2011 Journal of Nanotechnology in Engineering and Medicine  
mechanisms linked with musculoskeletal health disparities: stochastic models applying Tikhonov's theorem to biomolecule Homeostasis."  ...  Ongoing tissue engineering development studies have provided experimental input for biokinetic models examining the influence of static or dynamic mechanical  ...  In this model, the unknown dynamics associated with mechanical loading is incorporated as random (stochastic) loading on the anabolic and catabolic pathways through a perturbation of the growth factors  ... 
doi:10.1115/1.4003876 pmid:21743831 pmcid:PMC3131408 fatcat:wiujk4urmbezdcuspoo5jtv464

Modeling Strategic Route Choice and Real-Time Information Impacts in Stochastic and Time-Dependent Networks

Song Gao
2012 IEEE transactions on intelligent transportation systems (Print)  
This paper establishes a general framework to study the impacts of real-time information on users' routing decisions and the system cost in a stochastic time-dependent traffic network under a generalized  ...  Computational tests are carried out in a hypothetical network, where random incidents are the source of stochasticity.  ...  The demand-supply interaction in a stochastic dynamic network needs to be captured to answer the question.  ... 
doi:10.1109/tits.2012.2187197 fatcat:bswxyoe53zh4nm7m5rstl3muim

A stimulus-free graphical probabilistic switching model for sequential circuits using dynamic bayesian networks

Sanjukta Bhanja, Karthikeyan Lingasubramanian, N. Ranganathan
2006 ACM Transactions on Design Automation of Electronic Systems  
This model, which we refer to as the temporal dependency model (TDM), can be constructed from the logic structure and is shown to be a dynamic Bayesian Network.  ...  Dynamic Bayesian Networks are extremely powerful in modeling high order temporal as well as spatial correlations; it is an exact model for the underlying conditional independencies.  ...  We prove that the TDM structure is a Dynamic Bayesian Network (DBN) capturing all spatial and higher order temporal dependencies among the switchings in a sequential circuit.  ... 
doi:10.1145/1142980.1142990 fatcat:rzkxsjqtqzazjjrzymcakcqgki

Stochastic Model and Connectivity Dynamics for VANETs in Signalized Road Systems

Ivan Wang-Hei Ho, Kin K. Leung, John W. Polak
2011 IEEE/ACM Transactions on Networking  
We introduce in this paper a stochastic traffic model for VANETs in signalized urban road systems. The proposed model is a composite of the fluid model and stochastic model.  ...  As the key contribution of this paper, we attempt to approximate vehicle interactions and capture platoon formations and dissipations at traffic signals through a density-dependent velocity profile.  ...  STOCHASTIC MODEL In contrast to the deterministic fluid dynamic model, the stochastic model captures the stochastic fluctuations of the quantities of interest.  ... 
doi:10.1109/tnet.2010.2057257 fatcat:ohdaqd4cw5gapoyu2ofpjld5km

Hybrid Traffic Simulation with Adaptive Signal Control

Wilco Burghout, Johan Wahlstedt
2007 Transportation Research Record  
In this paper we implement and apply a hybrid mesoscopic-microscopic model that applies microscopic simulation to areas of specific interest, while simulating a large surrounding network in lesser detail  ...  The hybrid model is applied on a network where MEZZO simulates the entire Stockholm area (6000 links) and VISSIM simulates the area of specific interest containing three intersections with adaptive signal  ...  In addition, the authors thank Fredrik Davidsson (MOVEA) for providing the CONTRAM 8 network for Stockholm, which was used as a basis for the MEZZO network.  ... 
doi:10.3141/1999-20 fatcat:f5ugs4f5abeiti5yxbfktfkzjq

Distributed Optimization for Distribution Grids With Stochastic DER Using Multi-Agent Deep Reinforcement Learning

Mohammed Al-Saffar, Petr Musilek
2021 IEEE Access  
This article develops a special decomposition methodology for the traditional optimal power flow which facilitates optimal integration of stochastic distributed energy resources in power distribution systems  ...  First, two proposed algorithms, Dynamic Distributed Multi-Microgrid and Monte Carlo Tree Search based Reinforcement Learning, constitute dynamic microgrids of network nodes to confirm the electric power  ...  In addition, to deal with complex distribution circuits in stochastic environment, it is necessary to monitor network states and communicate them among the network buses.  ... 
doi:10.1109/access.2021.3075247 fatcat:jvixe7ham5bgfcm6ge3u774s5u

Using partial differential equations to model TCP mice and elephants in large IP networks

M.A. Marsan, M. Garetto, P. Giaccone, E. Leonardi, E. Schiattarella, A. Tarello
2005 IEEE/ACM Transactions on Networking  
In this paper we propose a new fluid model approach in which a different description of the dynamics of traffic sources is adopted, exploiting partial differential equations.  ...  This new description of the source dynamics allows the natural representation of short-lived as well as long-lived TCP connections, with no sacrifice in the scalability of the model.  ...  description of the stochastic network dynamics.  ... 
doi:10.1109/tnet.2005.860102 fatcat:wwctbtcxxbfp3o4zqxq7tnvhpa
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