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| Type: | Resource | |
| Storage: | The size of this resource is 206.3 KB | |
| Created: | Dec 11, 2018 at 9:41 p.m. (UTC) | |
| Last updated: | Sep 25, 2019 at 1:18 a.m. (UTC) (Metadata update) | |
| Published date: | Sep 25, 2019 at 1:18 a.m. (UTC) | |
| DOI: | 10.4211/hs.73b38d6417ac4352b9dae38a78a47d81 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 5293 |
| Downloads: | 613 |
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Abstract
This is a SWMM5 model that used for demonstrating swmm_mpc, a Python package for simulating model predictive control using SWMM5 as the process model. swmm_mpc is on github: https://github.com/UVAdMIST/swmm_mpc. To run these, you will need to install the swmm_mpc python package or use the Docker image according to the instructions on the github repo readme. This model was used as a demonstration in the following manuscript:
Sadler, J. M., Goodall, J. L., Behl, M., Morsy, M. M., Culver, T. B., & Bowes, B. D. (2019). Leveraging open source software and parallel computing for model predictive control of urban drainage systems using EPA-SWMM5. Environmental Modelling & Software, 120, 104484. https://doi.org/10.1016/j.envsoft.2019.07.009
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| This resource is described by | Sadler, J. M., Goodall, J. L., Behl, M., Morsy, M. M., Culver, T. B., & Bowes, B. D. (2019). Leveraging open source software and parallel computing for model predictive control of urban drainage systems using EPA-SWMM5. Environmental Modelling & Software, 120, 104484. https://doi.org/10.1016/j.envsoft.2019.07.009 |
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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