Suchergebnisse - Model Development – modeling methodologies. General Terms Algorithms

The Quest for the Best Explanation: Comparing Models and XAI Methods in Air Quality Modeling Tasks.

Autoren: Tasioulis, Thomas Bagkis, Evangelos Kassandros, Theodosios et al.

Quelle: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7390, 17p

Schlagwörter: AIR quality monitoring, ARTIFICIAL intelligence, PREDICTION models, PARTICULATE matter, FEATURE selection, MACHINE learning, DIMENSIONAL reduction algorithms

Geografische Kategorien: ASIA, BEIJING (China)

Automated Calibration of SWMM for Improved Stormwater Model Development and Application.

Autoren: Ahmadi, Hossein Scott, Durelle Sample, David J. et al.

Quelle: Hydrology (2306-5338); Jun2025, Vol. 12 Issue 6, p129-N.PAG, 26p

Schlagwörter: MULTI-objective optimization, STANDARD deviations, URBAN watersheds, OPTIMIZATION algorithms, URBAN runoff

Short-term salinity prediction for coastal areas of the Vietnamese Mekong Delta using various machine learning algorithms: a case study in Soc Trang Province.

Autoren: Dang, Le Thi Thanh Ishidaira, Hiroshi Nguyen, Ky Phung et al.

Quelle: Applied Water Science; Apr2025, Vol. 15 Issue 4, p1-25, 25p

Schlagwörter: SALINITY, MACHINE learning, SALTWATER encroachment, AGRICULTURE, COASTS, FORECASTING

Geografische Kategorien: VIETNAM

High-Resolution Interoperable Human-Friendly Naming System for Hydrographic Features and Model Elements (HRI-HydroName).

Autoren: Miles, Brian Saad, Haitham Habib, Emad

Quelle: Water (20734441); Oct2025, Vol. 17 Issue 19, p2900, 18p

Schlagwörter: HYDROLOGIC models, WATERSHEDS, MODEL-integrated computing, CLASSIFICATION

Rethinking Activated Sludge Modeling: A Critical Review of Modeling Strategies and the Role of Hybrid Integration.

Autoren: Zaveri J Li G Wang Z et al.

Quelle: Water environment research : a research publication of the Water Environment Federation [Water Environ Res] 2025 Oct; Vol. 97 (10), pp. e70181.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Wiley Subscription Services on behalf of The Water Environment Foundation Country of Publication: United States NLM ID: 9886167 Publication Model: Print Cited Medium: Internet ISSN: 1554-7531 (Electronic) Linking ISSN: 10614303 NLM ISO Abbreviation: Water Environ Res Subsets: MEDLINE

MeSH-Schlagworte: Sewage* , Waste Disposal, Fluid*/methods , Models, Theoretical*, Artificial Intelligence

When the whole is greater than the sum of its parts: why machine learning and conventional statistics are complementary for predicting future health outcomes Open Access.

Autoren: Janse, Roemer J Abu-Hanna, Ameen Vagliano, Iacopo et al.

Quelle: Clinical Kidney Journal; Apr2025, Vol. 18 Issue 4, p1-11, 11p

Schlagwörter: MACHINE learning, PREDICTION models, INTERDISCIPLINARY research, RANDOM forest algorithms, ARTIFICIAL intelligence, MATHEMATICAL statistics, SUPPORT vector machines

Accelerating Biologics PBPK Modelling with Automated Model Building: A Tutorial.

Autoren: Derbalah, Abdallah Abdulla, Tariq De Sousa Mendes, Mailys et al.

Quelle: Pharmaceutics; May2025, Vol. 17 Issue 5, p604, 28p

Schlagwörter: INDUSTRIALIZED building, THERAPEUTIC use of proteins, DRUG development, TRANSLATIONAL research, BIOLOGICALS

Analogues of Π Theorem via Machine Learning for Hydraulic Conveyance Laws.

Autoren: Chen, Hailiang Wang, Feifei Huai, Wenxin et al.

Quelle: Water Resources Research; Aug2025, Vol. 61 Issue 8, p1-19, 19p

Schlagwörter: PRINCIPAL components analysis, DIMENSIONAL reduction algorithms, FRICTION losses, DIMENSIONLESS numbers, MACHINE learning, PREDICTION models, FLUID mechanics, SCOUR (Hydraulic engineering)

Predictive Modeling for Electric Vehicle Battery State of Health: A Comprehensive Literature Review.

Autoren: Gong, Jianqiang Xu, Bin Chen, Fanghua et al.

Quelle: Energies (19961073); Jan2025, Vol. 18 Issue 2, p337, 37p

Schlagwörter: ELECTRIC vehicles, ELECTRIC vehicle industry, LITHIUM-ion batteries, MACHINE learning, PREDICTION models, ELECTRIC vehicle batteries

Behavioral Modeling of (Coupled) Harmonic Oscillators

Autoren: Piet Vanassche Georges The Pennsylvania State University CiteSeerX Archives

Weitere Verfasser: Piet Vanassche Georges The Pennsylvania State University CiteSeerX Archives

Quelle: http://www.sigda.org/Archives/ProceedingArchives/Dac/Dac2002/papers/2002/dac02/htmfiles/sun_sgi/././pdffiles/35_1.pdf.

Schlagwörter: I.6.5 [Computing Methodologies, Model Development— modeling methodologies General Terms Algorithms, Theory Keywords Averaging, Behavioral modeling, Coupled harmonic oscillators, Perturbation

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.7305; http://www.sigda.org/Archives/ProceedingArchives/Dac/Dac2002/papers/2002/dac02/htmfiles/sun_sgi/././pdffiles/35_1.pdf

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.7305
http://www.sigda.org/Archives/ProceedingArchives/Dac/Dac2002/papers/2002/dac02/htmfiles/sun_sgi/././pdffiles/35_1.pdf

Macro-models for high level area and power estimation on FPGAs

Autoren: Tianyi Jiang Xiaoyong Tang Prith Banerjee et al.

Weitere Verfasser: Tianyi Jiang Xiaoyong Tang Prith Banerjee et al.

Quelle: http://www.cs.york.ac.uk/rts/docs/SIGDA-Compendium-1994-2004/papers/2004/glsvlsi04/pdffiles/p162.pdf.

Schlagwörter: Categories and Subject Descriptors I.6.5 [Simulation and Modeling, Model Development – modeling methodologies. General Terms Algorithms, Design, Experimentation Keywords Model, High-level synthesis, RTL, Area estimation, Power estimation, FPGA

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.581.5274

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.581.5274
http://www.cs.york.ac.uk/rts/docs/SIGDA-Compendium-1994-2004/papers/2004/glsvlsi04/pdffiles/p162.pdf

Protocols for Water and Environmental Modeling Using Machine Learning in California.

Autoren: He, Minxue Sandhu, Prabhjot Namadi, Peyman et al.

Quelle: Hydrology (2306-5338); Mar2025, Vol. 12 Issue 3, p59, 45p

Schlagwörter: GENERATIVE artificial intelligence, MACHINE learning, ARTIFICIAL neural networks, ARTIFICIAL intelligence, QUALITY control

Geografische Kategorien: CALIFORNIA

A Fast Optical Propagation Technique for Modeling Micro-Optical Systems

Autoren: Timothy P. Kurzweg Steven P. Levitan Jose A. Martinez et al.

Weitere Verfasser: Timothy P. Kurzweg Steven P. Levitan Jose A. Martinez et al.

Quelle: http://www.sigda.org/Archives/ProceedingArchives/Dac/Dac2002/papers/2002/dac02/htmfiles/sun_sgi/././pdffiles/16_3.pdf.

Schlagwörter: Categories and Subject Descriptors I.6.5 [Simulation and Modeling, Model Development- modeling methodologies General Terms Algorithms, Design Keywords Optical Propagation, Angular Spectrum, CAD, Optical Micro-systems, Optical MEMS

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.1433; http://www.sigda.org/Archives/ProceedingArchives/Dac/Dac2002/papers/2002/dac02/htmfiles/sun_sgi/././pdffiles/16_3.pdf

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.1433
http://www.sigda.org/Archives/ProceedingArchives/Dac/Dac2002/papers/2002/dac02/htmfiles/sun_sgi/././pdffiles/16_3.pdf

Integrated Modeling of Hybrid Nanofiltration/Reverse Osmosis Desalination Plant Using Deep Learning-Based Crow Search Optimization Algorithm.

Autoren: Abba, Sani. I. Usman, Jamilu Abdulazeez, Ismail et al.

Quelle: Water (20734441); Oct2023, Vol. 15 Issue 19, p3515, 17p

Schlagwörter: DEEP learning, OPTIMIZATION algorithms, SALINE water conversion, REVERSE osmosis, SEARCH algorithms, NANOFILTRATION, STANDARD deviations

Research on Conductivity Mechanism and Saturation Model Development of Fractured‐Vuggy Carbonate Reservoirs.

Autoren: Wan, Jinbin Wei, Bo Zhang, Ni et al.

Quelle: Geofluids; 11/15/2025, Vol. 2025, p1-16, 16p

Schlagwörter: CARBONATE reservoirs, ELECTRIC conductivity, ROCK properties, ROCK analysis, POROSITY

Discovering additive structure in black box functions

Autoren: Giles Hooker The Pennsylvania State University CiteSeerX Archives

Weitere Verfasser: Giles Hooker The Pennsylvania State University CiteSeerX Archives

Quelle: http://www.bscb.cornell.edu/~hooker/VIN-kdd.pdf.

Schlagwörter: Modeling, Model Development—Modeling Methodologies General Terms Algorithms, Measurement, Design, Verification Keywords Visualization, Diagnostics, Functional ANOVA, Additive models, Graphical models, Interpretation, Feature Selection

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7500

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7500
http://www.bscb.cornell.edu/~hooker/VIN-kdd.pdf

Machine learning-based ensemble of Global climate models and trend analysis for projecting extreme precipitation indices under future climate scenarios.

Autoren: Kumar GP Dwarakish GS

Quelle: Environmental monitoring and assessment [Environ Monit Assess] 2025 Aug 12; Vol. 197 (9), pp. 1009. Date of Electronic Publication: 2025 Aug 12.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Springer Country of Publication: Netherlands NLM ID: 8508350 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-2959 (Electronic) Linking ISSN: 01676369 NLM ISO Abbreviation: Environ Monit Assess Subsets: MEDLINE

MeSH-Schlagworte: Climate Change* , Machine Learning* , Rain* , Environmental Monitoring*/methods , Climate Models*, India ; Forecasting ; Pattern Analysis, Machine

A Django-Based Modeling Platform for Predicting Soil Moisture in Agricultural Fields.

Autoren: Gan, Pengyu Gu, Zhe Zou, Hongyan et al.

Quelle: Water (20734441); Jun2025, Vol. 17 Issue 12, p1753, 15p

Schlagwörter: MACHINE learning, SOIL moisture, SOIL formation, PREDICTION models, AGRICULTURE

Predicting Stroke-Associated Pneumonia in Acute Ischemic Stroke: A Machine Learning Model Development and Validation Study with CBC-Derived Inflammatory Indices.

Autoren: Xie, Mengqi Liu, Zhiying Dai, Fangfang et al.

Quelle: International Journal of General Medicine; Jun2025, Vol. 18, p3117-3128, 12p

Schlagwörter: MACHINE learning, MONOCYTE lymphocyte ratio, ISCHEMIC stroke, PLATELET lymphocyte ratio, MODEL validation

Kankanhalli “Experience based Sampling Technique for Multimedia Analysis

Autoren: Jun Wang Mohan S Kankanhalli The Pennsylvania State University CiteSeerX Archives

Weitere Verfasser: Jun Wang Mohan S Kankanhalli The Pennsylvania State University CiteSeerX Archives

Quelle: http://www.comp.nus.edu.sg/~mohan/ebs/ExpSampling.pdf.

Schlagwörter: Color, Motion, Sensor fusion, Time-varying imagery. I.6.5. [Simulation and Modeling, Model Development- Modeling methodologies. General Terms Algorithms, Performance, Design, Experimentation

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.8840; http://www.comp.nus.edu.sg/~mohan/ebs/ExpSampling.pdf

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.8840
http://www.comp.nus.edu.sg/~mohan/ebs/ExpSampling.pdf