tag:joss.theoj.org,2005:/papers/tagged/system%20modeling?page=2Journal of Open Source Software2023-03-07T15:20:01ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/39892023-03-07T15:20:01Z2023-03-08T00:04:17ZWater Systems Integrated Modelling framework, WSIMOD: A Python package for integrated modelling of water quality and quantity across the water cycleaccepted0.2_joss_submission2022-11-07 18:03:22 UTC832023-03-07 15:20:01 UTC820234996BarnabyDobsonDepartment of Civil and Environmental Engineering, Imperial College London, UK0000-0002-0149-4124LeyangLiuDepartment of Civil and Environmental Engineering, Imperial College London, UK0000-0001-7556-1134AnaMijicDepartment of Civil and Environmental Engineering, Imperial College London, UK0000-0001-7096-940510.21105/joss.04996https://doi.org/10.5281/zenodo.7662569Pythonhttps://joss.theoj.org/papers/10.21105/joss.04996.pdfwater quality, hydrology, integrated modelling, pollutiontag:joss.theoj.org,2005:Paper/38372023-02-08T19:11:30Z2023-02-09T12:23:36ZCLOVER: A modelling framework for sustainable community-scale energy systemsacceptedv5.0.52022-08-25 18:43:55 UTC822023-02-08 19:11:30 UTC820234799PhilipSandwellDepartment of Physics, Blackett Laboratory, Imperial College London, SW7 2AZ, United Kingdom, Grantham Institute - Climate Change and the Environment, Imperial College London, SW7 2AZ, United Kingdom0000-0003-1117-5095BenedictWinchesterGrantham Institute - Climate Change and the Environment, Imperial College London, SW7 2AZ, United Kingdom, Department of Chemical Engineering, Imperial College London, SW7 2AZ, United Kingdom0000-0002-2880-1243HamishBeathDepartment of Physics, Blackett Laboratory, Imperial College London, SW7 2AZ, United Kingdom, Grantham Institute - Climate Change and the Environment, Imperial College London, SW7 2AZ, United Kingdom0000-0002-5124-9143JennyNelsonDepartment of Physics, Blackett Laboratory, Imperial College London, SW7 2AZ, United Kingdom, Grantham Institute - Climate Change and the Environment, Imperial College London, SW7 2AZ, United Kingdom0000-0003-1048-133010.21105/joss.04799https://doi.org/10.5281/zenodo.7575877Rich Text Format, Pythonhttps://joss.theoj.org/papers/10.21105/joss.04799.pdfenergy access, minigrid, renewable energy, sustainable developmenttag:joss.theoj.org,2005:Paper/39532022-12-15T20:15:45Z2022-12-26T14:53:41ZFreqAI: generalizing adaptive modeling for chaotic time-series market forecastsacceptedv1.02022-10-11 18:29:31 UTC802022-12-15 20:15:45 UTC720224864RobertA.CaulkEmergent Methods LLC, Arvada Colorado, 80005, USA, Freqtrade open source project0000-0001-5618-8629ElinTörnquistEmergent Methods LLC, Arvada Colorado, 80005, USA, Freqtrade open source project0000-0003-3289-8604MatthiasVoppichlerFreqtrade open source projectAndrewR.LawlessFreqtrade open source projectRyanMcMullanFreqtrade open source projectWagnerCostaSantosEmergent Methods LLC, Arvada Colorado, 80005, USA, Freqtrade open source projectTimothyC.PogueEmergent Methods LLC, Arvada Colorado, 80005, USA, Freqtrade open source projectJohanvan der VlugtFreqtrade open source projectStefanP.GehringFreqtrade open source projectPascalSchmidtFreqtrade open source project0000-0001-9328-434510.21105/joss.04864https://doi.org/10.5281/zenodo.7431513Pythonhttps://joss.theoj.org/papers/10.21105/joss.04864.pdfMachine Learning, adaptive modeling, chaotic systems, time-series forecastingtag:joss.theoj.org,2005:Paper/34412022-10-17T15:57:55Z2022-10-18T15:06:27ZPySD: System Dynamics Modeling in Pythonacceptedv2.2.42022-03-25 10:51:57 UTC782022-10-17 15:57:55 UTC720224329EnekoMartin-MartinezCREAF, Centre de Recerca Ecològica i Aplicacions Forestals, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain0000-0002-9213-7818RogerSamsóCREAF, Centre de Recerca Ecològica i Aplicacions Forestals, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain0000-0003-0348-3047JamesHoughtonComputational Social Science Lab, University of Pennsylvania, Philadelphia PA, 19104, United States of America0000-0002-6907-6973JordiSoléCREAF, Centre de Recerca Ecològica i Aplicacions Forestals, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain, Departament de Dinàmica de la Terra i l'Oceà, Universitat de Barcelona (UB) E08007, Catalonia, Spain0000-0002-2371-165210.21105/joss.04329https://doi.org/10.5281/zenodo.7094483Pythonhttps://joss.theoj.org/papers/10.21105/joss.04329.pdfSystem Dynamics, Vensim, Stellatag:joss.theoj.org,2005:Paper/30122022-08-28T17:42:36Z2022-09-05T12:15:23Zgdess: A framework for evaluating simulated atmospheric CO₂ in Earth System Modelsaccepted1.0.beta12021-09-03 10:35:11 UTC762022-08-28 17:42:36 UTC720224326DanielE.KaufmanJoint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA0000-0002-1487-7298ShaFengAtmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA0000-0002-2376-0868KatherineV.CalvinJoint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA0000-0003-2191-4189BryceE.HarropAtmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA0000-0003-3952-4525SusannahM.BurrowsAtmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA0000-0002-0745-725210.21105/joss.04326https://doi.org/10.5281/zenodo.6981643Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.04326.pdfEarth system model, atmospheric carbon dioxide, model evaluation, diagnosticstag:joss.theoj.org,2005:Paper/36402022-08-22T09:30:59Z2022-12-09T11:06:29ZMat-dp: An open-source Python model for analysing material demand projections and their environmental implications, which result from building low-carbon systems.acceptedv1.0.02022-06-02 14:15:48 UTC762022-08-22 09:30:59 UTC720224460KarlaCervantes BarronUniversity of Cambridge0000-0001-9185-3022JonathanM.CullenUniversity of Cambridge0000-0001-9367-179110.21105/joss.04460https://doi.org/10.5281/zenodo.7002733Pythonhttps://joss.theoj.org/papers/10.21105/joss.04460.pdfmaterials, python, low carbon, material efficiency, material demand, environmental implications, embodied emissionstag:joss.theoj.org,2005:Paper/30142022-07-05T20:37:08Z2022-07-06T00:01:04ZUnlockNN: Uncertainty quantification for neural network models of chemical systemsacceptedv2.0.22021-09-03 16:12:59 UTC752022-07-05 20:37:08 UTC720223700AlexanderMoriartyDepartment of Materials, Imperial College London, London, UK0000-0001-7525-1419KazukiMoritaDepartment of Materials, Imperial College London, London, UK0000-0002-2558-6963KeithT.ButlerSciML, STFC Scientific Computing Division, Rutherford Appleton Laboratories, UK0000-0001-5432-5597AronWalshDepartment of Materials, Imperial College London, London, UK, Department of Materials Science and Engineering, Yonsei University, Seoul, Korea0000-0001-5460-703310.21105/joss.03700https://doi.org/10.5281/zenodo.6799685Python, PureBasichttps://joss.theoj.org/papers/10.21105/joss.03700.pdfgraph neural networks, uncertainty quantification, machine learning, material science, chemistrytag:joss.theoj.org,2005:Paper/25472022-04-25T14:32:29Z2022-04-25T15:42:08ZPySDM v1: particle-based cloud modeling package for warm-rain microphysics and aqueous chemistryacceptedv12021-03-31 18:49:42 UTC722022-04-25 14:32:29 UTC720223219PiotrBartmanFaculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland0000-0003-0265-6428OleksiiBulenokFaculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland0000-0003-2272-8548KamilGórskiFaculty of Mathematics and Computer Science, Jagiellonian University, Kraków, PolandAnnaJarugaDepartment of Environmental Science and Engineering, California Institute of Technology, Pasadena, CA, USA0000-0003-3194-6440GrzegorzŁazarskiFaculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland, Faculty of Chemistry, Jagiellonian University, Kraków, Poland0000-0002-5595-371XMichaelA.OlesikFaculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Kraków, Poland0000-0002-6319-9358BartoszPiaseckiFaculty of Mathematics and Computer Science, Jagiellonian University, Kraków, PolandClareE.SingerDepartment of Environmental Science and Engineering, California Institute of Technology, Pasadena, CA, USA0000-0002-1708-0997AleksandraTalarFaculty of Mathematics and Computer Science, Jagiellonian University, Kraków, PolandSylwesterArabasUniversity of Illinois at Urbana-Champaign, Urbana, IL, USA, Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland0000-0003-2361-008210.21105/joss.03219https://doi.org/10.5281/zenodo.6321270Pythonhttps://joss.theoj.org/papers/10.21105/joss.03219.pdfphysics-simulation, monte-carlo-simulation, gpu-computing, atmospheric-modeling, particle-system, numba, thrust, nvrtc, pint, atmospheric-physicstag:joss.theoj.org,2005:Paper/31632022-02-05T08:41:42Z2022-02-06T00:00:29ZCacatoo: building, exploring, and sharing spatially structured models of biological systemsacceptedv1.0.02021-11-09 14:35:39 UTC702022-02-05 08:41:42 UTC720223948Bramvan DijkMax Planck Institute for Evolutionary Biology0000-0002-6330-693410.21105/joss.03948https://doi.org/10.5281/zenodo.5918404JavaScripthttps://joss.theoj.org/papers/10.21105/joss.03948.pdfjavascript, spatial structure, dynamics, individual-based models, microbial ecology and evolutiontag:joss.theoj.org,2005:Paper/31222022-01-29T01:16:01Z2022-01-30T00:01:12ZPySINDy: A comprehensive Python package for robust sparse system identificationacceptedv1.2.32021-10-21 18:46:09 UTC692022-01-29 01:16:01 UTC720223994AlanA.KaptanogluDepartment of Physics, University of WashingtonBrianM.de SilvaDepartment of Applied Mathematics, University of WashingtonUrbanFaselDepartment of Mechanical Engineering, University of WashingtonKadierdanKahemanDepartment of Mechanical Engineering, University of WashingtonAndyJ.GoldschmidtDepartment of Physics, University of WashingtonJaredCallahamDepartment of Mechanical Engineering, University of WashingtonCharlesB.DelahuntDepartment of Applied Mathematics, University of WashingtonZacharyG.NicolaouDepartment of Applied Mathematics, University of WashingtonKathleenChampionDepartment of Applied Mathematics, University of WashingtonJean-ChristopheLoiseauArts et Métiers Institute of Technology, CNAM, DynFluid, HESAM UniversitéJ.NathanKutzDepartment of Applied Mathematics, University of WashingtonStevenL.BruntonDepartment of Mechanical Engineering, University of Washington10.21105/joss.03994https://doi.org/10.5281/zenodo.5842612Pythonhttps://joss.theoj.org/papers/10.21105/joss.03994.pdfdynamical systems, sparse regression, model discovery, system identification, machine learning