Open-Source Modeling

Projects.OpenSourceModeling History

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* Hedengren, J.D., Nicholson, B., Open-Source Modeling Platforms, Keynote Talk at FOCAPO / CPC 2023, San Antonio, TX, 8-12 January 2023. [[https://apm.byu.edu/prism/uploads/Members/Hedengren2023.pdf|Paper]]
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* Hedengren, J.D., Nicholson, B., Open-Source Modeling Platforms, Keynote Talk at FOCAPO / CPC 2023, San Antonio, TX, 8-12 January 2023. [[https://apm.byu.edu/prism/uploads/Members/Hedengren2023.pdf|Paper]] | [[https://youtu.be/6YpENqAMB2A|Presentation]]
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# Gunnell, L., Nicholson, B., Hedengren, J.D., Equation-based and data-driven modeling: Open-source software current state and future directions, Computers & Chemical Engineering, 2024, 108521, ISSN 0098-1354, DOI: 10.1016/j.compchemeng.2023.108521. [[Attach:2023_Open_Source_Modeling.pdf|Preprint]] | [[https://www.sciencedirect.com/science/article/pii/S0098135423003915|Article]]
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* Gunnell, L., Nicholson, B., Hedengren, J.D., Equation-based and data-driven modeling: Open-source software current state and future directions, Computers & Chemical Engineering, 2024, 108521, ISSN 0098-1354, DOI: 10.1016/j.compchemeng.2023.108521. [[https://apm.byu.edu/prism/uploads/Members/2023_Open_Source_Modeling.pdf|Preprint]] | [[https://www.sciencedirect.com/science/article/pii/S0098135423003915|Article]]
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# Gunnell, L., Nicholson, B., Hedengren, J.D., Equation-based and data-driven modeling: Open-source software current state and future directions, Computers & Chemical Engineering, 2024, 108521, ISSN 0098-1354, DOI: 10.1016/j.compchemeng.2023.108521. [[Attach:2023_Open_Source_Modeling.pdf|Preprint]] | [[https://www.sciencedirect.com/science/article/pii/S0098135423003915|Article]]
February 03, 2023, at 07:38 PM by 10.35.117.248 -
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Propose a [[Main/NewProject|New Project]] to contribute technical or financial support for an open-source modeling platform.
February 03, 2023, at 06:54 PM by 10.35.117.248 -
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* Hedengren, J.D., Nicholson, B., Open-Source Modeling Platforms, Keynote Talk at FOCAPO / CPC 2023, San Antonio, TX, 8-12 January 2023. [[Attach:Hedengren2023.pdf|Paper]]
to:
* Hedengren, J.D., Nicholson, B., Open-Source Modeling Platforms, Keynote Talk at FOCAPO / CPC 2023, San Antonio, TX, 8-12 January 2023. [[https://apm.byu.edu/prism/uploads/Members/Hedengren2023.pdf|Paper]]
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Open-source modeling languages are essential tools for data analysis and scientific computing. Pyomo, Gekko, CasADi, and JuMP are mathematical programming languages for optimization problems. TensorFlow and PyTorch are used for machine learning and deep learning. JAX is a numerical library for high-performance machine learning research. Scikit-learn is a machine learning library for Python that provides simple and efficient tools for data mining and data analysis.
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Open-source modeling languages are essential tools for data analysis and scientific computing. Pyomo, Gekko, CasADi, and JuMP are mathematical programming languages for optimization problems. TensorFlow and PyTorch are used for machine learning and deep learning. JAX is a numerical library for high-performance machine learning research. Scikit-learn is a machine learning library for Python that provides simple and efficient tools for data mining and data analysis.
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!!!! Presentation
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!!!! Presentations
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<iframe width="560" height="315" src="https://www.youtube.com/embed/glWIzPPJRnQ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
February 03, 2023, at 06:44 PM by 10.35.117.248 -
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(:title Open-Source Modeling:)
(:keywords open-source, python, julia, optimization, modeling, JuMP, Gekko, pyomo, CasADi:)
(:description O:)

%width=550px%Attach:open_source_optimization.png

Open-source modeling languages are essential tools for data analysis and scientific computing. Pyomo, Gekko, CasADi, and JuMP are mathematical programming languages for optimization problems. TensorFlow and PyTorch are used for machine learning and deep learning. JAX is a numerical library for high-performance machine learning research. Scikit-learn is a machine learning library for Python that provides simple and efficient tools for data mining and data analysis.

!!!! Partnerships

The importance of a collaborative development effort in these open-source modeling languages cannot be overstated. Collaboration allows developers to pool their resources and knowledge, leading to faster and more robust development. Additionally, collaboration fosters a culture of sharing and support, helping to ensure the longevity and continued improvement of these essential tools.

* [[https://www.pnnl.gov|PNNL]] provides support for [[https://gekko.readthedocs.io/en/latest/ml.html|Physics-Informed Machine Learning]]
* [[https://www.seeq.com|Seeq]] provides support for [[https://github.com/BYU-PRISM/Seeq|Hybrid System Identification]] and PID Assessment packages.

!!!! Presentation

(:html:)
<iframe width="560" height="315" src="https://www.youtube.com/embed/6YpENqAMB2A" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
(:htmlend:)

!!!! Publications

* Hedengren, J.D., Nicholson, B., Open-Source Modeling Platforms, Keynote Talk at FOCAPO / CPC 2023, San Antonio, TX, 8-12 January 2023. [[Attach:Hedengren2023.pdf|Paper]]

* Gunnell, L., Manwaring, K., Lu, X., Reynolds, J., Vienna, J., Hedengren, J.D., Machine Learning with Gradient-based Optimization of Nuclear Waste Vitrification with Uncertainties and Constraints, Processes, 10(11), 2365, Nov 2022, DOI: 10.3390/pr10112365. [[https://www.mdpi.com/2227-9717/10/11/2365/htm|Article (Open Access)]] | [[https://gekko.readthedocs.io/en/latest/ml.html|Documentation]]