For decades, Discrete Choice Models (DCMs) have been used to describe, understand and predict human choice behaviour in a wide variety of contexts including transportation, healthcare and marketing. The field of discrete choice modelling is firmly rooted in economic theory, and most DCMs are based on the assumption that decision-makers, when asked to select an alternative among a set of presented alternatives, make deliberate trade-offs by employing a stable function to assign utility to each alternative, and then select the alternative with thehighest utility.TRAIL Thesis Series no. T2020/11, the Netherlands Research School TRAILTransport and Logistic
Since its inception, the choice modelling field has been dominated by theory-driven modelling approa...
Research in the field of artificial intelligence systems has been exploring the use of artificial ne...
© 2020 Elsevier Ltd Whereas deep neural network (DNN) is increasingly applied to choice analysis, it...
For decades, Discrete Choice Models (DCMs) have been used to describe, understand and predict human ...
Artificial Neural Networks (ANNs) are increasingly used for discrete choice analysis, being apprecia...
Artificial Intelligence in form of Machine Learning classifiers is increasingly applied for travel c...
In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and bi...
While deep neural networks (DNNs) have been increasingly applied to choice analysis showing high pre...
This electronic version was submitted by the student author. The certified thesis is available in th...
SIGLEAvailable from British Library Document Supply Centre- DSC:9025.959(OU-TSU--817) / BLDSC - Brit...
Classification methods from machine learning are receiving a lot of attention in the transportation ...
This study develops a novel Artificial Neural Network (ANN) based approach to investigate decision r...
Discrete choice models (DCMs) require a priori knowledge of the utility functions, especially how ta...
Background: Discrete choice models (DCMs) for moral choice analysis will likely lead to erroneous mo...
Researchers often treat data-driven and theory-driven models as two disparate or even conflicting me...
Since its inception, the choice modelling field has been dominated by theory-driven modelling approa...
Research in the field of artificial intelligence systems has been exploring the use of artificial ne...
© 2020 Elsevier Ltd Whereas deep neural network (DNN) is increasingly applied to choice analysis, it...
For decades, Discrete Choice Models (DCMs) have been used to describe, understand and predict human ...
Artificial Neural Networks (ANNs) are increasingly used for discrete choice analysis, being apprecia...
Artificial Intelligence in form of Machine Learning classifiers is increasingly applied for travel c...
In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and bi...
While deep neural networks (DNNs) have been increasingly applied to choice analysis showing high pre...
This electronic version was submitted by the student author. The certified thesis is available in th...
SIGLEAvailable from British Library Document Supply Centre- DSC:9025.959(OU-TSU--817) / BLDSC - Brit...
Classification methods from machine learning are receiving a lot of attention in the transportation ...
This study develops a novel Artificial Neural Network (ANN) based approach to investigate decision r...
Discrete choice models (DCMs) require a priori knowledge of the utility functions, especially how ta...
Background: Discrete choice models (DCMs) for moral choice analysis will likely lead to erroneous mo...
Researchers often treat data-driven and theory-driven models as two disparate or even conflicting me...
Since its inception, the choice modelling field has been dominated by theory-driven modelling approa...
Research in the field of artificial intelligence systems has been exploring the use of artificial ne...
© 2020 Elsevier Ltd Whereas deep neural network (DNN) is increasingly applied to choice analysis, it...