Operational route choice methodologies for practical applications

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Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

We study socio-political systems in representative democracies. Motivated by problems that affect the proper functioning of the system, we build computational methods to answer research questions regarding the phenomena occurring in them. For each phenomen ...

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical mod ...

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

Model and Data: Dujardin, J.; Lehning, M. Wind-Topo_model. EnviDat 2022 ...

The control possibilities for soft robots have long been hindered by the lack of accurate yet computationally treatable dynamic models of soft structures. Polynomial curvature models propose a solution to this quest for continuum slender structures. Nevert ...

Code generation is an effective way to drive the complex system development in model-based systems engineering. Currently, different code generators are developed for different modeling languages to deal with the development of systems with multi-domain. T ...

Oligopolistic competition occurs in various transportation markets. In this paper, we introduce a framework to find approximate equilibrium solutions of oligopolistic markets in which demand is modeled at the disaggregate level using discrete choice models ...

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...

Transformers have been proven a successful model for a variety of tasks in sequence modeling. However, computing the attention matrix, which is their key component, has quadratic complexity with respect to the sequence length, thus making them prohibitivel ...

The extremely high recognition accuracy achieved by modern, convolutional neural network (CNN) based face recognition (FR) systems has contributed significantly to the adoption of such systems in a variety of applications, from mundane activities like unlo ...

While the extant innovation literature has provided extensive evidence of the so-called "demand-pull" effect, the possible diverse impact of demand evolution on product vs process innovation activities has not been yet investigated. This paper develops a f ...

This paper is a study on the use of Machine Learning and Deep Learning to determine the similarity between different musics. The first part introduces the framework used and some concepts of Deep Learning that will be used in the algorithms. The second par ...

This article presents a new model for the main hydration peaks of tricalcium silicate and alite on the assumption that C-S-H nucleates and grows as needles. The model relies only on directly observable quantities and reproduces the transition from the acce ...

Increasing demand for new infrastructure and ageing of existing infrastructure has made management of infrastructure a key challenge of this century. Replacement of all ageing civil infrastructure is economically and environmentally unsustainable. Civil in ...

This thesis develops three models that study the motivation of various agents to take on debt, and the impact that excessive financial leverage can have on social welfare. In the chapter "Short-term Bank Leverage and the Value of Liquid Reserves", the ince ...

The Neurorobotics Platform of the Human Brain Project hosts many different large-scale models that can easily be connected with each other. Here, we linked a deep neural network for saliency computation to a spiking cortical model for visual segmentation ( ...

A large part of the research utilizing the concept of Macroscopic Fundamental Diagram (MFD) relies heavily on the PL model, an approximation of the trip completion rate derived for steady states. There exists an alternative method to the PL approximation. ...

Route choice analysis concerns the understanding, modeling and prediction of the itinerary of an individual who travels from one position to another. In this thesis we elaborate on aggregate route choice analysis. The objective is the development of a flex ...

Operational route choice methodologies for practical applications

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