RD
R.J. Dijkhuizen
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Short term traffic prediction using local information
Improving graph-based time series prediction using local information flows
This thesis presents localized methods for traffic prediction and analysis. The prediction method presents an extension of a state-of-the-art Graph Neural Network inspired by traffic flow characteristics on a local level. This inspiration from traffic flow characteristics consists of two parts. The first intuition is that state at some location and at time T in the future will be not influenced by information which is further than traveling time T away. The second intuition is that traffic information traveling with or against the stream of traffic behaves differently. The developed model leverages these intuitions to increase model prediction performance. Further, a modification is made which allows the model to be applied at an arbitrary location in a network, at the cost of performance. Alongside these model extensions, a novel method of visualizing a local traffic state is presented through constructing a novel traveltime diagram. This diagram can be used as a visual tool for analyzing traffic locally. Further, the traveltime diagram is designed to be summarized using Topological Data Analysis to a quantity called the Travel Lifetime which can represent traffic states ranging from extremely calm to imminent congestion to a congested state in a single number. The newly proposed Travel Lifetime is tested as an input to a Neural Network model for predicting traffic speed showing that its use as an input can improve model performance.
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This thesis presents localized methods for traffic prediction and analysis. The prediction method presents an extension of a state-of-the-art Graph Neural Network inspired by traffic flow characteristics on a local level. This inspiration from traffic flow characteristics consists of two parts. The first intuition is that state at some location and at time T in the future will be not influenced by information which is further than traveling time T away. The second intuition is that traffic information traveling with or against the stream of traffic behaves differently. The developed model leverages these intuitions to increase model prediction performance. Further, a modification is made which allows the model to be applied at an arbitrary location in a network, at the cost of performance. Alongside these model extensions, a novel method of visualizing a local traffic state is presented through constructing a novel traveltime diagram. This diagram can be used as a visual tool for analyzing traffic locally. Further, the traveltime diagram is designed to be summarized using Topological Data Analysis to a quantity called the Travel Lifetime which can represent traffic states ranging from extremely calm to imminent congestion to a congested state in a single number. The newly proposed Travel Lifetime is tested as an input to a Neural Network model for predicting traffic speed showing that its use as an input can improve model performance.
An exploration of the Kuramoto model
Mathematical background, links with physics and numerical analysis
Bachelor thesis
(2021)
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R.J. Dijkhuizen, J.L.A. Dubbeldam, J.M. Thijssen, Y.M. Blanter, E. Pulvirenti
This work is a bachelor thesis featuring a collection of explorations of the Kuramoto model in the presence of noise in one and two dimensions. The model was explored analytically and numerically. It contains a study of literature and new analytical derivations. An attempt to link the fraction of oscillators to the order parameter resulted in experience through the process of deriving the result, but a plot of the first few terms of this expansion showed it not being close. The assumption on which the expansion was based however was shown to be valid in simulations. More successfully an upper bound on the probability of synchronization was found. This probability was found on a ring consisting of N oscillators, and verified of a ring of 3 oscillators. The results was a bound better than one that was already calculated, though the method of verification used was not ideal. An analysis of the stability of solutions on this 3-ring resulted a visual representation of entrainment and an amount of stable solutions possible, which was 1. This result was in accordance with the more general result following from the investigation of a system of coupled rings with arbitrary sizes of either ring. We then expanded this system to conclude that the stability of the entire system could be split into the stability of either ring and the possibility of having a solution for the linking phase difference. We elaborated on general practices when numerically analyzing SDEs and integrations methods. The Kuramoto model proved to be kind in the sense that the Euler-forward and Milstein scheme coincided. In a more physics-centered approach we studied the Ising and XY model. This prompted literature study on the Kosterlitz Thouless transition, through analysing the spin-wave Hamiltonian and the energy of free vortex of a pair of vortices. We also then explored conservation of the vortex-pair behaviour in a noise including Kuramoto model, which verified a duality in partition functions as described in ref. [1].
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This work is a bachelor thesis featuring a collection of explorations of the Kuramoto model in the presence of noise in one and two dimensions. The model was explored analytically and numerically. It contains a study of literature and new analytical derivations. An attempt to link the fraction of oscillators to the order parameter resulted in experience through the process of deriving the result, but a plot of the first few terms of this expansion showed it not being close. The assumption on which the expansion was based however was shown to be valid in simulations. More successfully an upper bound on the probability of synchronization was found. This probability was found on a ring consisting of N oscillators, and verified of a ring of 3 oscillators. The results was a bound better than one that was already calculated, though the method of verification used was not ideal. An analysis of the stability of solutions on this 3-ring resulted a visual representation of entrainment and an amount of stable solutions possible, which was 1. This result was in accordance with the more general result following from the investigation of a system of coupled rings with arbitrary sizes of either ring. We then expanded this system to conclude that the stability of the entire system could be split into the stability of either ring and the possibility of having a solution for the linking phase difference. We elaborated on general practices when numerically analyzing SDEs and integrations methods. The Kuramoto model proved to be kind in the sense that the Euler-forward and Milstein scheme coincided. In a more physics-centered approach we studied the Ising and XY model. This prompted literature study on the Kosterlitz Thouless transition, through analysing the spin-wave Hamiltonian and the energy of free vortex of a pair of vortices. We also then explored conservation of the vortex-pair behaviour in a noise including Kuramoto model, which verified a duality in partition functions as described in ref. [1].