PUBLIKATIONSSERVER

Martin Kohlhase

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

26 Publikationen

Alle markieren

[26]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Technical Readiness of Prescriptive Analytics Platforms: A Survey
M. Niederhaus, N. Migenda, J. Weller, W. Schenck, M. Kohlhase, in: IEEE (Ed.), 2024 35th Conference of Open Innovations Association (FRUCT), IEEE, 2024, pp. 509–519.
HSBI-PUB | DOI
 
[25]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, R. Liu, A. Wegel, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, in: O. Niggemann, J. Beyerer, M. Krantz, C. Kühnert (Eds.), Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, Springer Nature Switzerland, Cham, 2024, pp. 89–100.
HSBI-PUB | DOI
 
[24]
2024 | Artikel | FH-PUB-ID: 4913
Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, Y. Naik, T. Heuwinkel, A. Kühn, M. Kohlhase, W. Schenck, R. Dumitrescu, Mathematics 12 (2024).
HSBI-PUB | DOI
 
[23]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories
J. Weller, N. Migenda, A. Wegel, M. Kohlhase, W. Schenck, R. Dumitrescu, in: IEEE (Ed.), 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), IEEE, 2023, pp. 1–7.
HSBI-PUB | DOI
 
[22]
2023 | Diskussionspapier | FH-PUB-ID: 3729 | OA
Benchmarking of Machine Learning Models for Tabular Scarce Data
J. Kösters, M. Schöne, M. Kohlhase, Benchmarking of Machine Learning Models for Tabular Scarce Data, n.d.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[21]
2023 | Konferenzbeitrag | FH-PUB-ID: 3713 | OA
Active Learning for Regression Problems with Ensemble Methods
B. Jaster, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 33. Workshop Computational Intelligence, Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29.
HSBI-PUB | DOI | Download (ext.)
 
[20]
2023 | Artikel | FH-PUB-ID: 2855 | OA
HUMANZENTRIERTE PRODUKTIONSPLANUNG MIT KI - Entwicklung eines Assistenzsystems
L. Vollenkemper, M. Mönikes, F. Wortmann, M. Rudolph-Puls, M. Kohlhase, A. Röchter, C. Ewering, Arbeitswelt.Plus Working Paper (2023).
HSBI-PUB | DOI | Download (ext.)
 
[19]
2023 | Artikel | FH-PUB-ID: 2849 | OA
Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops
L. Vollenkemper, F. Grumbach, M. Kohlhase, P. Reusch, Wt Werkstattstechnik Online 113 (2023) 158–163.
HSBI-PUB | DOI | Download (ext.)
 
[18]
2022 | Artikel | FH-PUB-ID: 1799 | OA
Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks
K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, W. Schenck, Sensors 22 (2022).
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[17]
2022 | Konferenzbeitrag | FH-PUB-ID: 2232
Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: H. Yin, D. Camacho, P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Springer International Publishing, Cham, 2022, pp. 379–390.
HSBI-PUB | DOI
 
[16]
2022 | Buchbeitrag | FH-PUB-ID: 2291 | OA
Analysis of the Behavior of Online Decision Trees Under Concept Drift at the Example of FIMT-DD
M. Hanitz, M. Schöne, T. Voigt, M. Kohlhase, in: P. Perner (Ed.), Machine Learning and Data Mining in Pattern Recognition, MLDM 2022, ibai-publishing, Leipzig, 2022, pp. 121–135.
HSBI-PUB | Download (ext.)
 
[15]
2022 | Konferenzbeitrag | FH-PUB-ID: 2277 | OA
Spatial Temporal Transformer Networks for Sparse Motion Capture Applications
L. Vollenkemper, M. Kohlhase, in: H. Schulte, F. Hoffman, R. Mikut, Karlsruhier Institut für Technologie (KIT) (Eds.), PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE, KIT Scientific Publishing, Karlsruhe, 2022.
HSBI-PUB | DOI | Download (ext.)
 
[14]
2021 | Konferenzbeitrag | FH-PUB-ID: 1912
Curvature-Oriented Splitting for Multivariate Model Trees
M. Schöne, M. Kohlhase, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2021, pp. 01–09.
HSBI-PUB | DOI | Download (ext.)
 
[13]
2021 | Konferenzbeitrag | FH-PUB-ID: 1560 | OA
Assistenzsystem zur Qualitätssicherung von IoT-Geräten basierend auf AutoML und SHAP
J. Ewerszumrode, M. Schöne, S. Godt, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 31. Workshop Computational Intelligence , KIT Scientific Publishing, 2021, pp. 285–305.
HSBI-PUB | DOI | Download (ext.)
 
[12]
2021 | Konferenzbeitrag | FH-PUB-ID: 3718
Space-Filling Designs for Experiments with Assembled Products
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 192–199.
HSBI-PUB | DOI | Download (ext.)
 
[11]
2021 | Artikel | FH-PUB-ID: 3717 | OA
Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge
T. Voigt, M. Kohlhase, O. Nelles, Mathematics 9 (2021).
HSBI-PUB | DOI | Download (ext.)
 
[10]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Advanced Data Analytics Platform for Manufacturing Companies
T. Voigt, N. Migenda, M. Schöne, D. Pelkmann, M. Fricke, W. Schenck, M. Kohlhase, in: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08.
HSBI-PUB | DOI
 
[9]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Variational Autoencoder based Novelty Detection for Real-World Time Series
L. Steinmann, N. Migenda, T. Voigt, M. Kohlhase, W. Schenck, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 1–7.
HSBI-PUB | DOI
 
[8]
2020 | Konferenzbeitrag | FH-PUB-ID: 1916
Least Squares Approach for Multivariate Split Selection in Regression Trees
M. Schöne, M. Kohlhase, in: C. Analide, P. Novais, D. Camacho, H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I, Springer International Publishing, Cham, 2020, pp. 41–50.
HSBI-PUB | DOI | Download (ext.)
 
[7]
2020 | Buchbeitrag | FH-PUB-ID: 1915 | OA
Least-Squares-Based Construction Algorithm for Oblique and Mixed Regression Trees
M. Schöne, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 30. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2020.
HSBI-PUB | DOI | Download (ext.)
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 1557
Identifikation eines nichtlinearen dynamischen Mehrgrößensystems mit rekurrenten neuronalen Netzen im Vergleich zu lokal-affinen Zustandsraummodellen
S. Godt, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 30. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2020, pp. 159–180.
HSBI-PUB | DOI
 
[5]
2020 | Konferenzbeitrag | FH-PUB-ID: 1367
Incremental Latin Hypercube Additive Design for LOLIMOT
T. Voigt, M. Kohlhase, O. Nelles, in: Institute of Electrical and Electronics Engineers (IEEE) (Ed.), 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2020, pp. 1602–1609.
HSBI-PUB | DOI
 
[4]
2020 | Artikel | FH-PUB-ID: 1368
Bestandsanlagen in der smarten Produktion, Integrationsstrategien anhand eines Praxisbeispiels
T. Voigt, M. Kohlhase, A. Peter, atp magazin 62 (2020) 62–69.
HSBI-PUB
 
[3]
2019 | Konferenzbeitrag | FH-PUB-ID: 1559 | OA
Data Mining im geschlossenen Regelkreis basierend auf adaptiven Kennfeldern mit integriertem Anti-Windup-Mechanismus
S. Godt, M. Kohlhase, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2019, pp. 51–72.
HSBI-PUB | DOI | Download (ext.)
 
[2]
2019 | Konferenzbeitrag | FH-PUB-ID: 1371
Inkrementelle Modellbildung von statischen Prozessen auf Basis von Latin Hypercube Designs
T. Voigt, M. Kohlhase, O. Nelles, in: Proceedings - 29. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2019, pp. 267–288.
HSBI-PUB
 
[1]
2018 | Konferenzbeitrag | FH-PUB-ID: 1369 | OA
Schätzung von datenbasierten lokal-linearen Modellen auf der Grundlage von LOLIMOT für den systematischen Entwurf von lokal-linearen Zustandsreglern
T. Voigt, M. Kohlhase, in: Proceedings - 28. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2018, pp. 93–111.
HSBI-PUB | Download (ext.)
 
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26 Publikationen

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[26]
2024 | Konferenzbeitrag | FH-PUB-ID: 4699
Technical Readiness of Prescriptive Analytics Platforms: A Survey
M. Niederhaus, N. Migenda, J. Weller, W. Schenck, M. Kohlhase, in: IEEE (Ed.), 2024 35th Conference of Open Innovations Association (FRUCT), IEEE, 2024, pp. 509–519.
HSBI-PUB | DOI
 
[25]
2024 | Buchbeitrag | FH-PUB-ID: 4915
Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, R. Liu, A. Wegel, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, in: O. Niggemann, J. Beyerer, M. Krantz, C. Kühnert (Eds.), Machine Learning for Cyber-Physical Systems. Selected Papers from the International Conference ML4CPS 2023, Springer Nature Switzerland, Cham, 2024, pp. 89–100.
HSBI-PUB | DOI
 
[24]
2024 | Artikel | FH-PUB-ID: 4913
Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories
J. Weller, N. Migenda, Y. Naik, T. Heuwinkel, A. Kühn, M. Kohlhase, W. Schenck, R. Dumitrescu, Mathematics 12 (2024).
HSBI-PUB | DOI
 
[23]
2023 | Konferenzbeitrag | FH-PUB-ID: 4700
Conceptual Framework for Prescriptive Analytics Based on Decision Theory in Smart Factories
J. Weller, N. Migenda, A. Wegel, M. Kohlhase, W. Schenck, R. Dumitrescu, in: IEEE (Ed.), 2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), IEEE, 2023, pp. 1–7.
HSBI-PUB | DOI
 
[22]
2023 | Diskussionspapier | FH-PUB-ID: 3729 | OA
Benchmarking of Machine Learning Models for Tabular Scarce Data
J. Kösters, M. Schöne, M. Kohlhase, Benchmarking of Machine Learning Models for Tabular Scarce Data, n.d.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[21]
2023 | Konferenzbeitrag | FH-PUB-ID: 3713 | OA
Active Learning for Regression Problems with Ensemble Methods
B. Jaster, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 33. Workshop Computational Intelligence, Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29.
HSBI-PUB | DOI | Download (ext.)
 
[20]
2023 | Artikel | FH-PUB-ID: 2855 | OA
HUMANZENTRIERTE PRODUKTIONSPLANUNG MIT KI - Entwicklung eines Assistenzsystems
L. Vollenkemper, M. Mönikes, F. Wortmann, M. Rudolph-Puls, M. Kohlhase, A. Röchter, C. Ewering, Arbeitswelt.Plus Working Paper (2023).
HSBI-PUB | DOI | Download (ext.)
 
[19]
2023 | Artikel | FH-PUB-ID: 2849 | OA
Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops
L. Vollenkemper, F. Grumbach, M. Kohlhase, P. Reusch, Wt Werkstattstechnik Online 113 (2023) 158–163.
HSBI-PUB | DOI | Download (ext.)
 
[18]
2022 | Artikel | FH-PUB-ID: 1799 | OA
Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks
K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, W. Schenck, Sensors 22 (2022).
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[17]
2022 | Konferenzbeitrag | FH-PUB-ID: 2232
Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: H. Yin, D. Camacho, P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Springer International Publishing, Cham, 2022, pp. 379–390.
HSBI-PUB | DOI
 
[16]
2022 | Buchbeitrag | FH-PUB-ID: 2291 | OA
Analysis of the Behavior of Online Decision Trees Under Concept Drift at the Example of FIMT-DD
M. Hanitz, M. Schöne, T. Voigt, M. Kohlhase, in: P. Perner (Ed.), Machine Learning and Data Mining in Pattern Recognition, MLDM 2022, ibai-publishing, Leipzig, 2022, pp. 121–135.
HSBI-PUB | Download (ext.)
 
[15]
2022 | Konferenzbeitrag | FH-PUB-ID: 2277 | OA
Spatial Temporal Transformer Networks for Sparse Motion Capture Applications
L. Vollenkemper, M. Kohlhase, in: H. Schulte, F. Hoffman, R. Mikut, Karlsruhier Institut für Technologie (KIT) (Eds.), PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE, KIT Scientific Publishing, Karlsruhe, 2022.
HSBI-PUB | DOI | Download (ext.)
 
[14]
2021 | Konferenzbeitrag | FH-PUB-ID: 1912
Curvature-Oriented Splitting for Multivariate Model Trees
M. Schöne, M. Kohlhase, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2021, pp. 01–09.
HSBI-PUB | DOI | Download (ext.)
 
[13]
2021 | Konferenzbeitrag | FH-PUB-ID: 1560 | OA
Assistenzsystem zur Qualitätssicherung von IoT-Geräten basierend auf AutoML und SHAP
J. Ewerszumrode, M. Schöne, S. Godt, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 31. Workshop Computational Intelligence , KIT Scientific Publishing, 2021, pp. 285–305.
HSBI-PUB | DOI | Download (ext.)
 
[12]
2021 | Konferenzbeitrag | FH-PUB-ID: 3718
Space-Filling Designs for Experiments with Assembled Products
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 192–199.
HSBI-PUB | DOI | Download (ext.)
 
[11]
2021 | Artikel | FH-PUB-ID: 3717 | OA
Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge
T. Voigt, M. Kohlhase, O. Nelles, Mathematics 9 (2021).
HSBI-PUB | DOI | Download (ext.)
 
[10]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Advanced Data Analytics Platform for Manufacturing Companies
T. Voigt, N. Migenda, M. Schöne, D. Pelkmann, M. Fricke, W. Schenck, M. Kohlhase, in: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08.
HSBI-PUB | DOI
 
[9]
2021 | Konferenzbeitrag | FH-PUB-ID: 2572
Variational Autoencoder based Novelty Detection for Real-World Time Series
L. Steinmann, N. Migenda, T. Voigt, M. Kohlhase, W. Schenck, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 1–7.
HSBI-PUB | DOI
 
[8]
2020 | Konferenzbeitrag | FH-PUB-ID: 1916
Least Squares Approach for Multivariate Split Selection in Regression Trees
M. Schöne, M. Kohlhase, in: C. Analide, P. Novais, D. Camacho, H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I, Springer International Publishing, Cham, 2020, pp. 41–50.
HSBI-PUB | DOI | Download (ext.)
 
[7]
2020 | Buchbeitrag | FH-PUB-ID: 1915 | OA
Least-Squares-Based Construction Algorithm for Oblique and Mixed Regression Trees
M. Schöne, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 30. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2020.
HSBI-PUB | DOI | Download (ext.)
 
[6]
2020 | Konferenzbeitrag | FH-PUB-ID: 1557
Identifikation eines nichtlinearen dynamischen Mehrgrößensystems mit rekurrenten neuronalen Netzen im Vergleich zu lokal-affinen Zustandsraummodellen
S. Godt, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 30. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2020, pp. 159–180.
HSBI-PUB | DOI
 
[5]
2020 | Konferenzbeitrag | FH-PUB-ID: 1367
Incremental Latin Hypercube Additive Design for LOLIMOT
T. Voigt, M. Kohlhase, O. Nelles, in: Institute of Electrical and Electronics Engineers (IEEE) (Ed.), 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2020, pp. 1602–1609.
HSBI-PUB | DOI
 
[4]
2020 | Artikel | FH-PUB-ID: 1368
Bestandsanlagen in der smarten Produktion, Integrationsstrategien anhand eines Praxisbeispiels
T. Voigt, M. Kohlhase, A. Peter, atp magazin 62 (2020) 62–69.
HSBI-PUB
 
[3]
2019 | Konferenzbeitrag | FH-PUB-ID: 1559 | OA
Data Mining im geschlossenen Regelkreis basierend auf adaptiven Kennfeldern mit integriertem Anti-Windup-Mechanismus
S. Godt, M. Kohlhase, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2019, pp. 51–72.
HSBI-PUB | DOI | Download (ext.)
 
[2]
2019 | Konferenzbeitrag | FH-PUB-ID: 1371
Inkrementelle Modellbildung von statischen Prozessen auf Basis von Latin Hypercube Designs
T. Voigt, M. Kohlhase, O. Nelles, in: Proceedings - 29. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2019, pp. 267–288.
HSBI-PUB
 
[1]
2018 | Konferenzbeitrag | FH-PUB-ID: 1369 | OA
Schätzung von datenbasierten lokal-linearen Modellen auf der Grundlage von LOLIMOT für den systematischen Entwurf von lokal-linearen Zustandsreglern
T. Voigt, M. Kohlhase, in: Proceedings - 28. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2018, pp. 93–111.
HSBI-PUB | Download (ext.)
 
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