PUBLIKATIONSSERVER

Martin Kohlhase

https://orcid.org/0009-0002-9374-0720

28 Publikationen

Alle markieren

[28]
2024 | Konferenzbeitrag | FH-PUB-ID: 5789
Dockhorn, Frederick-Mortimer, and Martin Kohlhase. “An Application-Oriented Review of Standard and Integral Sparse Identification of Nonlinear Dynamics.” Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024, edited by Horst Schulte et al., KIT Scientific Publishing, 2024, pp. 53–76, doi:10.5445/KSP/1000174544.
HSBI-PUB | DOI
 
[27]
2024 | Artikel | FH-PUB-ID: 5497
Weller, Julian, et al. “Design Decisions for Integrating Prescriptive Analytics Use Cases into Smart Factories.” Procedia CIRP, vol. 128, Elsevier BV, 2024, pp. 424–29, doi:10.1016/j.procir.2024.03.022.
HSBI-PUB | DOI
 
[26]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Niederhaus, Marvin, et al. “Technical Readiness of Prescriptive Analytics Platforms: A Survey.” 2024 35th Conference of Open Innovations Association (FRUCT), edited by IEEE, IEEE, 2024, pp. 509–19, doi:10.23919/FRUCT61870.2024.10516367.
HSBI-PUB | DOI
 
[25]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Weller, Julian, et al. “Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories.” Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, edited by Oliver Niggemann et al., vol. 18, Springer Nature Switzerland, 2024, pp. 89–100, doi:10.1007/978-3-031-47062-2_9.
HSBI-PUB | DOI
 
[24]
2024 | Artikel | FH-PUB-ID: 4913
Weller, Julian, et al. “Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories.” Mathematics, vol. 12, no. 17, 2663, MDPI AG, 2024, doi:10.3390/math12172663.
HSBI-PUB | DOI
 
[23]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Weller, Julian, et al. “Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories.” 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), edited by IEEE, IEEE, 2023, pp. 1–7, doi:10.1109/ADACIS59737.2023.10424368.
HSBI-PUB | DOI
 
[22]
2023 | Diskussionspapier | FH-PUB-ID: 3729 | OA
Kösters, Justus, et al. Benchmarking of Machine Learning Models for Tabular Scarce Data.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[21]
2023 | Konferenzbeitrag | FH-PUB-ID: 3713 | OA
Jaster, Bjarne, and Martin Kohlhase. “Active Learning for Regression Problems with Ensemble Methods.” Proceedings - 33. Workshop Computational Intelligence, edited by Horst Schulte et al., Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29, doi:10.5445/KSP/1000162754.
HSBI-PUB | DOI | Download (ext.)
 
[20]
2023 | Artikel | FH-PUB-ID: 2855 | OA
Vollenkemper, Lukas, et al. “HUMANZENTRIERTE PRODUKTIONSPLANUNG MIT KI - Entwicklung Eines Assistenzsystems.” Arbeitswelt.Plus Working Paper, it’s OWL Clustermanagement GmbH, 2023, doi:10.55594/UXIT4205.
HSBI-PUB | DOI | Download (ext.)
 
[19]
2023 | Artikel | FH-PUB-ID: 2849 | OA
Vollenkemper, Lukas, et al. “Humanzentrierte Ablaufplanung von Montagelinien/Human-Centered Scheduling in Assembly Lines - Plug and Play: Efficient Algorithms Minimize Stress in Flow Shops.” Wt Werkstattstechnik Online, vol. 113, no. 04, VDI Fachmedien GmbH and Co. KG, 2023, pp. 158–63, doi:10.37544/1436-4980-2023-04-58.
HSBI-PUB | DOI | Download (ext.)
 
[18]
2022 | Artikel | FH-PUB-ID: 1799 | OA
Vandevoorde, Koenraad, et al. “Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks.” Sensors, vol. 22, no. 7, 2481, MDPI AG, 2022, doi:10.3390/s22072481.
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[17]
2022 | Konferenzbeitrag | FH-PUB-ID: 2232
Voigt, Tim, et al. “Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes.” Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, edited by Hujun Yin et al., Springer International Publishing, 2022, pp. 379–90, doi:10.1007/978-3-031-21753-1_37.
HSBI-PUB | DOI
 
[16]
2022 | Buchbeitrag | FH-PUB-ID: 2291 | OA
Hanitz, Marcel, et al. “Analysis of the Behavior of Online Decision Trees Under Concept Drift at the Example of FIMT-DD.” Machine Learning and Data Mining in Pattern Recognition, MLDM 2022, edited by Petra Perner, ibai-publishing, 2022, pp. 121–35.
HSBI-PUB | Download (ext.)
 
[15]
2022 | Konferenzbeitrag | FH-PUB-ID: 2277 | OA
Vollenkemper, Lukas, and Martin Kohlhase. “Spatial Temporal Transformer Networks for Sparse Motion Capture Applications.” PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE, edited by Horst Schulte et al., vol. 32, KIT Scientific Publishing, 2022, doi:10.5445/KSP/1000151141.
HSBI-PUB | DOI | Download (ext.)
 
[14]
2021 | Konferenzbeitrag | FH-PUB-ID: 1912
Schöne, Marvin, and Martin Kohlhase. “Curvature-Oriented Splitting for Multivariate Model Trees.” 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2021, pp. 01–09, doi:10.1109/SSCI50451.2021.9659858.
HSBI-PUB | DOI | Download (ext.)
 
[13]
2021 | Konferenzbeitrag | FH-PUB-ID: 1560 | OA
Ewerszumrode, Jan, et al. “Assistenzsystem zur Qualitätssicherung von IoT-Geräten basierend auf AutoML und SHAP.” Proceedings - 31. Workshop Computational Intelligence , edited by Horst Schulte et al., KIT Scientific Publishing, 2021, pp. 285–305, doi:10.5445/KSP/1000138532.
HSBI-PUB | DOI | Download (ext.)
 
[12]
2021 | Konferenzbeitrag | FH-PUB-ID: 3718
Voigt, Tim, et al. “Space-Filling Designs for Experiments with Assembled Products.” 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, 2021, pp. 192–99, doi:10.1145/3460824.3460854.
HSBI-PUB | DOI | Download (ext.)
 
[11]
2021 | Artikel | FH-PUB-ID: 3717 | OA
Voigt, Tim, et al. “Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge.” Mathematics, vol. 9, no. 19, 2479, MDPI AG, 2021, doi:10.3390/math9192479.
HSBI-PUB | DOI | Download (ext.)
 
[10]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Voigt, Tim, et al. “Advanced Data Analytics Platform for Manufacturing Companies.” 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08, doi:10.1109/ETFA45728.2021.9613499.
HSBI-PUB | DOI
 
[9]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Steinmann, Luca, et al. “Variational Autoencoder Based Novelty Detection for Real-World Time Series.” 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, 2021, pp. 1–7, doi:10.1145/3460824.3460825.
HSBI-PUB | DOI
 
[8]
2020 | Konferenzbeitrag | FH-PUB-ID: 1916
Schöne, Marvin, and Martin Kohlhase. “Least Squares Approach for Multivariate Split Selection in Regression Trees.” Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I, edited by Cesar Analide et al., Springer International Publishing, 2020, pp. 41–50, doi:10.1007/978-3-030-62362-3_5.
HSBI-PUB | DOI | Download (ext.)
 
[7]
2020 | Buchbeitrag | FH-PUB-ID: 1915 | OA
Schöne, Marvin, and Martin Kohlhase. “Least-Squares-Based Construction Algorithm for Oblique and Mixed Regression Trees.” Proceedings - 30. Workshop Computational Intelligence, edited by Horst Schulte et al., KIT Scientific Publishing, 2020, doi:10.5445/KSP/1000124139.
HSBI-PUB | DOI | Download (ext.)
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 1557
Godt, Stephan, and Martin Kohlhase. “Identifikation eines nichtlinearen dynamischen Mehrgrößensystems mit rekurrenten neuronalen Netzen im Vergleich zu lokal-affinen Zustandsraummodellen.” Proceedings - 30. Workshop Computational Intelligence, edited by Horst Schulte et al., KIT Scientific Publishing, 2020, pp. 159–80, doi:10.5445/KSP/1000124139.
HSBI-PUB | DOI
 
[5]
2020 | Konferenzbeitrag | FH-PUB-ID: 1367
Voigt, Tim, et al. “Incremental Latin Hypercube Additive Design for LOLIMOT.” 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), edited by Institute of Electrical and Electronics Engineers (IEEE), IEEE, 2020, pp. 1602–09, doi:10.1109/ETFA46521.2020.9212173.
HSBI-PUB | DOI
 
[4]
2020 | Artikel | FH-PUB-ID: 1368
Voigt, Tim, et al. “Bestandsanlagen in der smarten Produktion, Integrationsstrategien anhand eines Praxisbeispiels.” atp magazin, vol. 62, no. 04, 2020, pp. 62–69.
HSBI-PUB
 
[3]
2019 | Konferenzbeitrag | FH-PUB-ID: 1371 | OA
Voigt, Tim, et al. “Inkrementelle Modellbildung von statischen Prozessen auf Basis von Latin Hypercube Designs.” Proceedings - 29. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2019, pp. 267–88, doi:10.5445/KSP/1000098736.
HSBI-PUB | DOI | Download (ext.)
 
[2]
2019 | Konferenzbeitrag | FH-PUB-ID: 1559 | OA
Godt, Stephan, and Martin Kohlhase. “Data Mining im geschlossenen Regelkreis basierend auf adaptiven Kennfeldern mit integriertem Anti-Windup-Mechanismus.” Proceedings - 29. Workshop Computational Intelligence, edited by Frank Hoffmann et al., KIT Scientific Publishing, 2019, pp. 51–72, doi:10.5445/KSP/1000098736.
HSBI-PUB | DOI | Download (ext.)
 
[1]
2018 | Konferenzbeitrag | FH-PUB-ID: 1369 | OA
Voigt, Tim, and Martin Kohlhase. “Schätzung von datenbasierten lokal-linearen Modellen auf der Grundlage von LOLIMOT für den systematischen Entwurf von lokal-linearen Zustandsreglern.” Proceedings - 28. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2018, pp. 93–111.
HSBI-PUB | Download (ext.)
 
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Zitationsstil: MLA

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28 Publikationen

Alle markieren

[28]
2024 | Konferenzbeitrag | FH-PUB-ID: 5789
Dockhorn, Frederick-Mortimer, and Martin Kohlhase. “An Application-Oriented Review of Standard and Integral Sparse Identification of Nonlinear Dynamics.” Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024, edited by Horst Schulte et al., KIT Scientific Publishing, 2024, pp. 53–76, doi:10.5445/KSP/1000174544.
HSBI-PUB | DOI
 
[27]
2024 | Artikel | FH-PUB-ID: 5497
Weller, Julian, et al. “Design Decisions for Integrating Prescriptive Analytics Use Cases into Smart Factories.” Procedia CIRP, vol. 128, Elsevier BV, 2024, pp. 424–29, doi:10.1016/j.procir.2024.03.022.
HSBI-PUB | DOI
 
[26]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Niederhaus, Marvin, et al. “Technical Readiness of Prescriptive Analytics Platforms: A Survey.” 2024 35th Conference of Open Innovations Association (FRUCT), edited by IEEE, IEEE, 2024, pp. 509–19, doi:10.23919/FRUCT61870.2024.10516367.
HSBI-PUB | DOI
 
[25]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Weller, Julian, et al. “Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories.” Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, edited by Oliver Niggemann et al., vol. 18, Springer Nature Switzerland, 2024, pp. 89–100, doi:10.1007/978-3-031-47062-2_9.
HSBI-PUB | DOI
 
[24]
2024 | Artikel | FH-PUB-ID: 4913
Weller, Julian, et al. “Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories.” Mathematics, vol. 12, no. 17, 2663, MDPI AG, 2024, doi:10.3390/math12172663.
HSBI-PUB | DOI
 
[23]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Weller, Julian, et al. “Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories.” 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), edited by IEEE, IEEE, 2023, pp. 1–7, doi:10.1109/ADACIS59737.2023.10424368.
HSBI-PUB | DOI
 
[22]
2023 | Diskussionspapier | FH-PUB-ID: 3729 | OA
Kösters, Justus, et al. Benchmarking of Machine Learning Models for Tabular Scarce Data.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[21]
2023 | Konferenzbeitrag | FH-PUB-ID: 3713 | OA
Jaster, Bjarne, and Martin Kohlhase. “Active Learning for Regression Problems with Ensemble Methods.” Proceedings - 33. Workshop Computational Intelligence, edited by Horst Schulte et al., Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29, doi:10.5445/KSP/1000162754.
HSBI-PUB | DOI | Download (ext.)
 
[20]
2023 | Artikel | FH-PUB-ID: 2855 | OA
Vollenkemper, Lukas, et al. “HUMANZENTRIERTE PRODUKTIONSPLANUNG MIT KI - Entwicklung Eines Assistenzsystems.” Arbeitswelt.Plus Working Paper, it’s OWL Clustermanagement GmbH, 2023, doi:10.55594/UXIT4205.
HSBI-PUB | DOI | Download (ext.)
 
[19]
2023 | Artikel | FH-PUB-ID: 2849 | OA
Vollenkemper, Lukas, et al. “Humanzentrierte Ablaufplanung von Montagelinien/Human-Centered Scheduling in Assembly Lines - Plug and Play: Efficient Algorithms Minimize Stress in Flow Shops.” Wt Werkstattstechnik Online, vol. 113, no. 04, VDI Fachmedien GmbH and Co. KG, 2023, pp. 158–63, doi:10.37544/1436-4980-2023-04-58.
HSBI-PUB | DOI | Download (ext.)
 
[18]
2022 | Artikel | FH-PUB-ID: 1799 | OA
Vandevoorde, Koenraad, et al. “Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks.” Sensors, vol. 22, no. 7, 2481, MDPI AG, 2022, doi:10.3390/s22072481.
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[17]
2022 | Konferenzbeitrag | FH-PUB-ID: 2232
Voigt, Tim, et al. “Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes.” Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, edited by Hujun Yin et al., Springer International Publishing, 2022, pp. 379–90, doi:10.1007/978-3-031-21753-1_37.
HSBI-PUB | DOI
 
[16]
2022 | Buchbeitrag | FH-PUB-ID: 2291 | OA
Hanitz, Marcel, et al. “Analysis of the Behavior of Online Decision Trees Under Concept Drift at the Example of FIMT-DD.” Machine Learning and Data Mining in Pattern Recognition, MLDM 2022, edited by Petra Perner, ibai-publishing, 2022, pp. 121–35.
HSBI-PUB | Download (ext.)
 
[15]
2022 | Konferenzbeitrag | FH-PUB-ID: 2277 | OA
Vollenkemper, Lukas, and Martin Kohlhase. “Spatial Temporal Transformer Networks for Sparse Motion Capture Applications.” PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE, edited by Horst Schulte et al., vol. 32, KIT Scientific Publishing, 2022, doi:10.5445/KSP/1000151141.
HSBI-PUB | DOI | Download (ext.)
 
[14]
2021 | Konferenzbeitrag | FH-PUB-ID: 1912
Schöne, Marvin, and Martin Kohlhase. “Curvature-Oriented Splitting for Multivariate Model Trees.” 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2021, pp. 01–09, doi:10.1109/SSCI50451.2021.9659858.
HSBI-PUB | DOI | Download (ext.)
 
[13]
2021 | Konferenzbeitrag | FH-PUB-ID: 1560 | OA
Ewerszumrode, Jan, et al. “Assistenzsystem zur Qualitätssicherung von IoT-Geräten basierend auf AutoML und SHAP.” Proceedings - 31. Workshop Computational Intelligence , edited by Horst Schulte et al., KIT Scientific Publishing, 2021, pp. 285–305, doi:10.5445/KSP/1000138532.
HSBI-PUB | DOI | Download (ext.)
 
[12]
2021 | Konferenzbeitrag | FH-PUB-ID: 3718
Voigt, Tim, et al. “Space-Filling Designs for Experiments with Assembled Products.” 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, 2021, pp. 192–99, doi:10.1145/3460824.3460854.
HSBI-PUB | DOI | Download (ext.)
 
[11]
2021 | Artikel | FH-PUB-ID: 3717 | OA
Voigt, Tim, et al. “Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge.” Mathematics, vol. 9, no. 19, 2479, MDPI AG, 2021, doi:10.3390/math9192479.
HSBI-PUB | DOI | Download (ext.)
 
[10]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Voigt, Tim, et al. “Advanced Data Analytics Platform for Manufacturing Companies.” 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08, doi:10.1109/ETFA45728.2021.9613499.
HSBI-PUB | DOI
 
[9]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Steinmann, Luca, et al. “Variational Autoencoder Based Novelty Detection for Real-World Time Series.” 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, 2021, pp. 1–7, doi:10.1145/3460824.3460825.
HSBI-PUB | DOI
 
[8]
2020 | Konferenzbeitrag | FH-PUB-ID: 1916
Schöne, Marvin, and Martin Kohlhase. “Least Squares Approach for Multivariate Split Selection in Regression Trees.” Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I, edited by Cesar Analide et al., Springer International Publishing, 2020, pp. 41–50, doi:10.1007/978-3-030-62362-3_5.
HSBI-PUB | DOI | Download (ext.)
 
[7]
2020 | Buchbeitrag | FH-PUB-ID: 1915 | OA
Schöne, Marvin, and Martin Kohlhase. “Least-Squares-Based Construction Algorithm for Oblique and Mixed Regression Trees.” Proceedings - 30. Workshop Computational Intelligence, edited by Horst Schulte et al., KIT Scientific Publishing, 2020, doi:10.5445/KSP/1000124139.
HSBI-PUB | DOI | Download (ext.)
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 1557
Godt, Stephan, and Martin Kohlhase. “Identifikation eines nichtlinearen dynamischen Mehrgrößensystems mit rekurrenten neuronalen Netzen im Vergleich zu lokal-affinen Zustandsraummodellen.” Proceedings - 30. Workshop Computational Intelligence, edited by Horst Schulte et al., KIT Scientific Publishing, 2020, pp. 159–80, doi:10.5445/KSP/1000124139.
HSBI-PUB | DOI
 
[5]
2020 | Konferenzbeitrag | FH-PUB-ID: 1367
Voigt, Tim, et al. “Incremental Latin Hypercube Additive Design for LOLIMOT.” 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), edited by Institute of Electrical and Electronics Engineers (IEEE), IEEE, 2020, pp. 1602–09, doi:10.1109/ETFA46521.2020.9212173.
HSBI-PUB | DOI
 
[4]
2020 | Artikel | FH-PUB-ID: 1368
Voigt, Tim, et al. “Bestandsanlagen in der smarten Produktion, Integrationsstrategien anhand eines Praxisbeispiels.” atp magazin, vol. 62, no. 04, 2020, pp. 62–69.
HSBI-PUB
 
[3]
2019 | Konferenzbeitrag | FH-PUB-ID: 1371 | OA
Voigt, Tim, et al. “Inkrementelle Modellbildung von statischen Prozessen auf Basis von Latin Hypercube Designs.” Proceedings - 29. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2019, pp. 267–88, doi:10.5445/KSP/1000098736.
HSBI-PUB | DOI | Download (ext.)
 
[2]
2019 | Konferenzbeitrag | FH-PUB-ID: 1559 | OA
Godt, Stephan, and Martin Kohlhase. “Data Mining im geschlossenen Regelkreis basierend auf adaptiven Kennfeldern mit integriertem Anti-Windup-Mechanismus.” Proceedings - 29. Workshop Computational Intelligence, edited by Frank Hoffmann et al., KIT Scientific Publishing, 2019, pp. 51–72, doi:10.5445/KSP/1000098736.
HSBI-PUB | DOI | Download (ext.)
 
[1]
2018 | Konferenzbeitrag | FH-PUB-ID: 1369 | OA
Voigt, Tim, and Martin Kohlhase. “Schätzung von datenbasierten lokal-linearen Modellen auf der Grundlage von LOLIMOT für den systematischen Entwurf von lokal-linearen Zustandsreglern.” Proceedings - 28. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2018, pp. 93–111.
HSBI-PUB | Download (ext.)
 
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Darstellung / Sortierung

Zitationsstil: MLA

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