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pro vyhledávání: '"Yazdizadeh, Ali"'
Multi-task learning is assumed as a powerful inference method, specifically, where there is a considerable correlation between multiple tasks, predicting them in an unique framework may enhance prediction results. This research challenges this assump
Externí odkaz:
http://arxiv.org/abs/2110.12113
Autor:
Yazdizadeh, Ali, Farooq, Bilal
Ontology is the explicit and formal representation of the concepts in a domain and relations among them. Transportation science is a wide domain dealing with mobility over various complex and interconnected transportation systems, such as land, aviat
Externí odkaz:
http://arxiv.org/abs/2012.08622
We develop ensemble Convolutional Neural Networks (CNNs) to classify the transportation mode of trip data collected as part of a large-scale smartphone travel survey in Montreal, Canada. Our proposed ensemble library is composed of a series of CNN mo
Externí odkaz:
http://arxiv.org/abs/1904.08933
Publikováno v:
Journal of Big Data Analytics in Transportation, 2021
Semi-supervised Generative Adversarial Networks (GANs) are developed in the context of travel mode inference with uni-dimensional smartphone trajectory data. We use data from a large-scale smartphone travel survey in Montreal, Canada. We convert GPS
Externí odkaz:
http://arxiv.org/abs/1902.10768
Publikováno v:
In International Journal of Transportation Science and Technology March 2019 8(1):82-100
Publikováno v:
In Landscape and Urban Planning January 2017 157:63-74
Autor:
Nickkar, Amirreza1 amirreza.nickkar@morgan.edu, Yazdizadeh, Ali2 ali.yazdizadeh@concordia.ca, Young-Jae Lee1 YoungJae.Lee@morgan.edu
Publikováno v:
Advances in Transportation Studies. Nov2020, Issue 52, p131-142. 12p.
Akademický článek
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Publikováno v:
Journal of Big Data Analytics in Transportation; 20210101, Issue: Preprints p1-11, 11p
Publikováno v:
2015 5th International Youth Conference on Energy (IYCE); 2015, p1-6, 6p