Time Series Forecasting
Data collection and processing scripts
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Scope And Content | Scripts for data collection, data analysis, machine learning, visualization, etc. |
Technical Details | See environment.yml in the .zip file for details about channels, dependencies, and packages. |
Time series deep learning library
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Scope And Content | Time series deep learning library developed during project. |
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[tool.poetry.dependencies] |
Input data
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Scope And Content | Input data from sources listed in related resources. |
Output data
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Scope And Content | Model predictions derived from scripts in DSE_MAS_group3_project_repo.zip. |
- Collection
- Cite This Work
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Gupta, Aparna; Lane, Kevin; Martinez, Raul; Roten, Daniel; Shah, Akash; Yu, Rose (2021). Time Series Forecasting. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J03F4PHC
- Description
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From the onset of the COVID-19 pandemic, a dramatic change in traffic patterns has been observed across the country due to travel and other restrictions imposed by government agencies and health experts. The causes for these abrupt changes can be at least partially attributed to the severity of the pandemic, the widespread increase in remote work and online learning, business closures, etc. Considering these changes, we hypothesize that the performance of static time series models used for traffic forecasting will degrade beginning in early 2020. Dynamic models that do not rely solely on historical information will better forecast day-to-day traffic and be able to learn long-term changes in traffic patterns. We present a graph convolutional recurrent neural network that captures both the inherent spatial and temporal complexities present in traffic forecasting. The algorithm is part of a larger deep learning library for time series modeling being developed for the open-source community.
- Creation Date
- 2021-01 to 2021-06
- Date Issued
- 2021
- Advisor
- Contributors
- Series
- Topics
Formats
View formats within this collection
- Language
- English
- Identifier
- Related Resources
- Caltrans Performance Measurement System (PeMS). https://pems.dot.ca.gov/?dnode=Clearinghouse
- COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. https://github.com/CSSEGISandData/COVID-19
- Department of Transportation freeway coordinates. https://data-usdot.opendata.arcgis.com/documents/usdot::census-tiger-line-roads/about
- Diffusion Convolutional Recurrent Neural Network (DCRNN) implementation in PyTorch: https://github.com/chnsh/DCRNN_PyTorch
Source data
Previous version
- License
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Creative Commons Attribution 4.0 International Public License
- Rights Holder
- Gupta, Aparna; Lane, Kevin; Martinez, Raul; Roten, Daniel; Shah, Akash
- Copyright
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Under copyright (US)
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
- Digital Object Made Available By
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Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
- Last Modified
2024-02-27