---
_id: '6315'
article_number: '3669'
author:
- first_name: Kanat
  full_name: Suleimenov, Kanat
  last_name: Suleimenov
- first_name: Akim
  full_name: Kapsalyamov, Akim
  id: '257451'
  last_name: Kapsalyamov
  orcid: 0000-0003-3700-6214
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-3700-6214/work/197758764
- first_name: Beibit
  full_name: Abdikenov, Beibit
  last_name: Abdikenov
- first_name: Aiman
  full_name: Ozhikenova, Aiman
  last_name: Ozhikenova
- first_name: Yerbolat
  full_name: Igembay, Yerbolat
  last_name: Igembay
- first_name: Kassymbek
  full_name: Ozhikenov, Kassymbek
  last_name: Ozhikenov
citation:
  alphadin: '<span style="font-variant:small-caps;">Suleimenov, Kanat</span> ; <span
    style="font-variant:small-caps;">Kapsalyamov, Akim</span> ; <span style="font-variant:small-caps;">Abdikenov,
    Beibit</span> ; <span style="font-variant:small-caps;">Ozhikenova, Aiman</span>
    ; <span style="font-variant:small-caps;">Igembay, Yerbolat</span> ; <span style="font-variant:small-caps;">Ozhikenov,
    Kassymbek</span>: Comparative Analysis of Model-Based and Data-Driven Control
    for Tendon-Driven Robotic Fingers. In: <i>Mathematics</i> Bd. 13, MDPI AG (2025),
    Nr. 22'
  ama: Suleimenov K, Kapsalyamov A, Abdikenov B, Ozhikenova A, Igembay Y, Ozhikenov
    K. Comparative Analysis of Model-Based and Data-Driven Control for Tendon-Driven
    Robotic Fingers. <i>Mathematics</i>. 2025;13(22). doi:<a href="https://doi.org/10.3390/math13223669">10.3390/math13223669</a>
  apa: Suleimenov, K., Kapsalyamov, A., Abdikenov, B., Ozhikenova, A., Igembay, Y.,
    &#38; Ozhikenov, K. (2025). Comparative Analysis of Model-Based and Data-Driven
    Control for Tendon-Driven Robotic Fingers. <i>Mathematics</i>, <i>13</i>(22).
    <a href="https://doi.org/10.3390/math13223669">https://doi.org/10.3390/math13223669</a>
  bibtex: '@article{Suleimenov_Kapsalyamov_Abdikenov_Ozhikenova_Igembay_Ozhikenov_2025,
    title={Comparative Analysis of Model-Based and Data-Driven Control for Tendon-Driven
    Robotic Fingers}, volume={13}, DOI={<a href="https://doi.org/10.3390/math13223669">10.3390/math13223669</a>},
    number={223669}, journal={Mathematics}, publisher={MDPI AG}, author={Suleimenov,
    Kanat and Kapsalyamov, Akim and Abdikenov, Beibit and Ozhikenova, Aiman and Igembay,
    Yerbolat and Ozhikenov, Kassymbek}, year={2025} }'
  chicago: Suleimenov, Kanat, Akim Kapsalyamov, Beibit Abdikenov, Aiman Ozhikenova,
    Yerbolat Igembay, and Kassymbek Ozhikenov. “Comparative Analysis of Model-Based
    and Data-Driven Control for Tendon-Driven Robotic Fingers.” <i>Mathematics</i>
    13, no. 22 (2025). <a href="https://doi.org/10.3390/math13223669">https://doi.org/10.3390/math13223669</a>.
  ieee: K. Suleimenov, A. Kapsalyamov, B. Abdikenov, A. Ozhikenova, Y. Igembay, and
    K. Ozhikenov, “Comparative Analysis of Model-Based and Data-Driven Control for
    Tendon-Driven Robotic Fingers,” <i>Mathematics</i>, vol. 13, no. 22, 2025.
  mla: Suleimenov, Kanat, et al. “Comparative Analysis of Model-Based and Data-Driven
    Control for Tendon-Driven Robotic Fingers.” <i>Mathematics</i>, vol. 13, no. 22,
    3669, MDPI AG, 2025, doi:<a href="https://doi.org/10.3390/math13223669">10.3390/math13223669</a>.
  short: K. Suleimenov, A. Kapsalyamov, B. Abdikenov, A. Ozhikenova, Y. Igembay, K.
    Ozhikenov, Mathematics 13 (2025).
date_created: 2025-11-24T10:25:13Z
date_updated: 2026-03-17T15:29:29Z
doi: 10.3390/math13223669
intvolume: '        13'
issue: '22'
language:
- iso: eng
project:
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
publication: Mathematics
publication_identifier:
  eissn:
  - 2227-7390
publication_status: published
publisher: MDPI AG
status: public
title: Comparative Analysis of Model-Based and Data-Driven Control for Tendon-Driven
  Robotic Fingers
type: journal_article
user_id: '257451'
volume: 13
year: '2025'
...
---
_id: '4913'
article_number: '2663'
author:
- first_name: Julian
  full_name: Weller, Julian
  last_name: Weller
- first_name: Nico
  full_name: Migenda, Nico
  id: '218473'
  last_name: Migenda
  orcid: 0000-0002-7223-1735
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0002-7223-1735/work/167155079
- first_name: Yash
  full_name: Naik, Yash
  last_name: Naik
- first_name: Tim
  full_name: Heuwinkel, Tim
  last_name: Heuwinkel
- first_name: Arno
  full_name: Kühn, Arno
  last_name: Kühn
- first_name: Martin
  full_name: Kohlhase, Martin
  id: '226669'
  last_name: Kohlhase
  orcid: 0009-0002-9374-0720
  orcid_put_code_url: https://api.orcid.org/v2.0/0009-0002-9374-0720/work/167155080
- first_name: Wolfram
  full_name: Schenck, Wolfram
  id: '224375'
  last_name: Schenck
  orcid: 0000-0003-3300-2048
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-3300-2048/work/167155081
- first_name: Roman
  full_name: Dumitrescu, Roman
  last_name: Dumitrescu
citation:
  alphadin: '<span style="font-variant:small-caps;">Weller, Julian</span> ; <span
    style="font-variant:small-caps;">Migenda, Nico</span> ; <span style="font-variant:small-caps;">Naik,
    Yash</span> ; <span style="font-variant:small-caps;">Heuwinkel, Tim</span> ; <span
    style="font-variant:small-caps;">Kühn, Arno</span> ; <span style="font-variant:small-caps;">Kohlhase,
    Martin</span> ; <span style="font-variant:small-caps;">Schenck, Wolfram</span>
    ; <span style="font-variant:small-caps;">Dumitrescu, Roman</span>: Reference Architecture
    for the Integration of Prescriptive Analytics Use Cases in Smart Factories. In:
    <i>Mathematics</i> Bd. 12, MDPI AG (2024), Nr. 17'
  ama: Weller J, Migenda N, Naik Y, et al. Reference Architecture for the Integration
    of Prescriptive Analytics Use Cases in Smart Factories. <i>Mathematics</i>. 2024;12(17).
    doi:<a href="https://doi.org/10.3390/math12172663">10.3390/math12172663</a>
  apa: Weller, J., Migenda, N., Naik, Y., Heuwinkel, T., Kühn, A., Kohlhase, M., …
    Dumitrescu, R. (2024). Reference Architecture for the Integration of Prescriptive
    Analytics Use Cases in Smart Factories. <i>Mathematics</i>, <i>12</i>(17). <a
    href="https://doi.org/10.3390/math12172663">https://doi.org/10.3390/math12172663</a>
  bibtex: '@article{Weller_Migenda_Naik_Heuwinkel_Kühn_Kohlhase_Schenck_Dumitrescu_2024,
    title={Reference Architecture for the Integration of Prescriptive Analytics Use
    Cases in Smart Factories}, volume={12}, DOI={<a href="https://doi.org/10.3390/math12172663">10.3390/math12172663</a>},
    number={172663}, journal={Mathematics}, publisher={MDPI AG}, author={Weller, Julian
    and Migenda, Nico and Naik, Yash and Heuwinkel, Tim and Kühn, Arno and Kohlhase,
    Martin and Schenck, Wolfram and Dumitrescu, Roman}, year={2024} }'
  chicago: Weller, Julian, Nico Migenda, Yash Naik, Tim Heuwinkel, Arno Kühn, Martin
    Kohlhase, Wolfram Schenck, and Roman Dumitrescu. “Reference Architecture for the
    Integration of Prescriptive Analytics Use Cases in Smart Factories.” <i>Mathematics</i>
    12, no. 17 (2024). <a href="https://doi.org/10.3390/math12172663">https://doi.org/10.3390/math12172663</a>.
  ieee: J. Weller <i>et al.</i>, “Reference Architecture for the Integration of Prescriptive
    Analytics Use Cases in Smart Factories,” <i>Mathematics</i>, vol. 12, no. 17,
    2024.
  mla: Weller, Julian, et al. “Reference Architecture for the Integration of Prescriptive
    Analytics Use Cases in Smart Factories.” <i>Mathematics</i>, vol. 12, no. 17,
    2663, MDPI AG, 2024, doi:<a href="https://doi.org/10.3390/math12172663">10.3390/math12172663</a>.
  short: J. Weller, N. Migenda, Y. Naik, T. Heuwinkel, A. Kühn, M. Kohlhase, W. Schenck,
    R. Dumitrescu, Mathematics 12 (2024).
date_created: 2024-09-10T07:26:47Z
date_updated: 2026-03-17T15:29:08Z
doi: 10.3390/math12172663
intvolume: '        12'
issue: '17'
language:
- iso: eng
project:
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
- _id: f432a2ee-bceb-11ed-a251-a83585c5074d
  name: Institute for Data Science Solutions
publication: Mathematics
publication_identifier:
  eissn:
  - 2227-7390
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: Reference Architecture for the Integration of Prescriptive Analytics Use Cases
  in Smart Factories
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: '224375'
volume: 12
year: '2024'
...
---
_id: '2774'
article_number: '820'
author:
- first_name: Alaa
  full_name: Tharwat, Alaa
  id: '238549'
  last_name: Tharwat
- first_name: Wolfram
  full_name: Schenck, Wolfram
  id: '224375'
  last_name: Schenck
  orcid: 0000-0003-3300-2048
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-3300-2048/work/177802462
citation:
  alphadin: '<span style="font-variant:small-caps;">Tharwat, Alaa</span> ; <span style="font-variant:small-caps;">Schenck,
    Wolfram</span>: A Survey on Active Learning: State-of-the-Art, Practical Challenges
    and Research Directions. In: <i>Mathematics</i> Bd. 11, MDPI AG (2023), Nr. 4'
  ama: 'Tharwat A, Schenck W. A Survey on Active Learning: State-of-the-Art, Practical
    Challenges and Research Directions. <i>Mathematics</i>. 2023;11(4). doi:<a href="https://doi.org/10.3390/math11040820">10.3390/math11040820</a>'
  apa: 'Tharwat, A., &#38; Schenck, W. (2023). A Survey on Active Learning: State-of-the-Art,
    Practical Challenges and Research Directions. <i>Mathematics</i>, <i>11</i>(4).
    <a href="https://doi.org/10.3390/math11040820">https://doi.org/10.3390/math11040820</a>'
  bibtex: '@article{Tharwat_Schenck_2023, title={A Survey on Active Learning: State-of-the-Art,
    Practical Challenges and Research Directions}, volume={11}, DOI={<a href="https://doi.org/10.3390/math11040820">10.3390/math11040820</a>},
    number={4820}, journal={Mathematics}, publisher={MDPI AG}, author={Tharwat, Alaa
    and Schenck, Wolfram}, year={2023} }'
  chicago: 'Tharwat, Alaa, and Wolfram Schenck. “A Survey on Active Learning: State-of-the-Art,
    Practical Challenges and Research Directions.” <i>Mathematics</i> 11, no. 4 (2023).
    <a href="https://doi.org/10.3390/math11040820">https://doi.org/10.3390/math11040820</a>.'
  ieee: 'A. Tharwat and W. Schenck, “A Survey on Active Learning: State-of-the-Art,
    Practical Challenges and Research Directions,” <i>Mathematics</i>, vol. 11, no.
    4, 2023.'
  mla: 'Tharwat, Alaa, and Wolfram Schenck. “A Survey on Active Learning: State-of-the-Art,
    Practical Challenges and Research Directions.” <i>Mathematics</i>, vol. 11, no.
    4, 820, MDPI AG, 2023, doi:<a href="https://doi.org/10.3390/math11040820">10.3390/math11040820</a>.'
  short: A. Tharwat, W. Schenck, Mathematics 11 (2023).
date_created: 2023-04-18T21:54:19Z
date_updated: 2026-03-17T15:28:37Z
department:
- _id: '103'
doi: 10.3390/math11040820
intvolume: '        11'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/2227-7390/11/4/820
oa: '1'
project:
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
publication: Mathematics
publication_identifier:
  eissn:
  - 2227-7390
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: 'A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research
  Directions'
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: '249224'
volume: 11
year: '2023'
...
---
_id: '2775'
article_number: '1068'
author:
- first_name: Alaa
  full_name: Tharwat, Alaa
  id: '238549'
  last_name: Tharwat
- first_name: Wolfram
  full_name: Schenck, Wolfram
  id: '224375'
  last_name: Schenck
  orcid: 0000-0003-3300-2048
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-3300-2048/work/177802451
citation:
  alphadin: '<span style="font-variant:small-caps;">Tharwat, Alaa</span> ; <span style="font-variant:small-caps;">Schenck,
    Wolfram</span>: A Novel Low-Query-Budget Active Learner with Pseudo-Labels for
    Imbalanced Data. In: <i>Mathematics</i> Bd. 10, MDPI AG (2022), Nr. 7'
  ama: Tharwat A, Schenck W. A Novel Low-Query-Budget Active Learner with Pseudo-Labels
    for Imbalanced Data. <i>Mathematics</i>. 2022;10(7). doi:<a href="https://doi.org/10.3390/math10071068">10.3390/math10071068</a>
  apa: Tharwat, A., &#38; Schenck, W. (2022). A Novel Low-Query-Budget Active Learner
    with Pseudo-Labels for Imbalanced Data. <i>Mathematics</i>, <i>10</i>(7). <a href="https://doi.org/10.3390/math10071068">https://doi.org/10.3390/math10071068</a>
  bibtex: '@article{Tharwat_Schenck_2022, title={A Novel Low-Query-Budget Active Learner
    with Pseudo-Labels for Imbalanced Data}, volume={10}, DOI={<a href="https://doi.org/10.3390/math10071068">10.3390/math10071068</a>},
    number={71068}, journal={Mathematics}, publisher={MDPI AG}, author={Tharwat, Alaa
    and Schenck, Wolfram}, year={2022} }'
  chicago: Tharwat, Alaa, and Wolfram Schenck. “A Novel Low-Query-Budget Active Learner
    with Pseudo-Labels for Imbalanced Data.” <i>Mathematics</i> 10, no. 7 (2022).
    <a href="https://doi.org/10.3390/math10071068">https://doi.org/10.3390/math10071068</a>.
  ieee: A. Tharwat and W. Schenck, “A Novel Low-Query-Budget Active Learner with Pseudo-Labels
    for Imbalanced Data,” <i>Mathematics</i>, vol. 10, no. 7, 2022.
  mla: Tharwat, Alaa, and Wolfram Schenck. “A Novel Low-Query-Budget Active Learner
    with Pseudo-Labels for Imbalanced Data.” <i>Mathematics</i>, vol. 10, no. 7, 1068,
    MDPI AG, 2022, doi:<a href="https://doi.org/10.3390/math10071068">10.3390/math10071068</a>.
  short: A. Tharwat, W. Schenck, Mathematics 10 (2022).
date_created: 2023-04-18T21:54:20Z
date_updated: 2026-03-17T15:28:37Z
doi: 10.3390/math10071068
intvolume: '        10'
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/2227-7390/10/7/1068
oa: '1'
publication: Mathematics
publication_identifier:
  eissn:
  - 2227-7390
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: A Novel Low-Query-Budget Active Learner with Pseudo-Labels for Imbalanced Data
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: '249224'
volume: 10
year: '2022'
...
---
_id: '1730'
article_number: '932'
author:
- first_name: David
  full_name: Leserri, David
  last_name: Leserri
- first_name: Nils
  full_name: Grimmelsmann, Nils
  id: '214493'
  last_name: Grimmelsmann
  orcid: 0000-0002-4864-4978
- first_name: Malte
  full_name: Mechtenberg, Malte
  id: '218573'
  last_name: Mechtenberg
  orcid: 0000-0002-8958-0931
- first_name: Hanno Gerd
  full_name: Meyer, Hanno Gerd
  id: '231466'
  last_name: Meyer
  orcid: 0000-0003-2454-3897
- first_name: Axel
  full_name: Schneider, Axel
  id: '213480'
  last_name: Schneider
  orcid: 0000-0002-6632-3473
citation:
  alphadin: '<span style="font-variant:small-caps;">Leserri, David</span> ; <span
    style="font-variant:small-caps;">Grimmelsmann, Nils</span> ; <span style="font-variant:small-caps;">Mechtenberg,
    Malte</span> ; <span style="font-variant:small-caps;">Meyer, Hanno Gerd</span>
    ; <span style="font-variant:small-caps;">Schneider, Axel</span>: Evaluation of
    sEMG Signal Features and Segmentation Parameters for Limb Movement Prediction
    Using a Feedforward Neural Network. In: <i>Mathematics</i> Bd. 10, MDPI AG (2022),
    Nr. 6'
  ama: Leserri D, Grimmelsmann N, Mechtenberg M, Meyer HG, Schneider A. Evaluation
    of sEMG Signal Features and Segmentation Parameters for Limb Movement Prediction
    Using a Feedforward Neural Network. <i>Mathematics</i>. 2022;10(6). doi:<a href="https://doi.org/10.3390/math10060932">10.3390/math10060932</a>
  apa: Leserri, D., Grimmelsmann, N., Mechtenberg, M., Meyer, H. G., &#38; Schneider,
    A. (2022). Evaluation of sEMG Signal Features and Segmentation Parameters for
    Limb Movement Prediction Using a Feedforward Neural Network. <i>Mathematics</i>,
    <i>10</i>(6). <a href="https://doi.org/10.3390/math10060932">https://doi.org/10.3390/math10060932</a>
  bibtex: '@article{Leserri_Grimmelsmann_Mechtenberg_Meyer_Schneider_2022, title={Evaluation
    of sEMG Signal Features and Segmentation Parameters for Limb Movement Prediction
    Using a Feedforward Neural Network}, volume={10}, DOI={<a href="https://doi.org/10.3390/math10060932">10.3390/math10060932</a>},
    number={6932}, journal={Mathematics}, publisher={MDPI AG}, author={Leserri, David
    and Grimmelsmann, Nils and Mechtenberg, Malte and Meyer, Hanno Gerd and Schneider,
    Axel}, year={2022} }'
  chicago: Leserri, David, Nils Grimmelsmann, Malte Mechtenberg, Hanno Gerd Meyer,
    and Axel Schneider. “Evaluation of SEMG Signal Features and Segmentation Parameters
    for Limb Movement Prediction Using a Feedforward Neural Network.” <i>Mathematics</i>
    10, no. 6 (2022). <a href="https://doi.org/10.3390/math10060932">https://doi.org/10.3390/math10060932</a>.
  ieee: D. Leserri, N. Grimmelsmann, M. Mechtenberg, H. G. Meyer, and A. Schneider,
    “Evaluation of sEMG Signal Features and Segmentation Parameters for Limb Movement
    Prediction Using a Feedforward Neural Network,” <i>Mathematics</i>, vol. 10, no.
    6, 2022.
  mla: Leserri, David, et al. “Evaluation of SEMG Signal Features and Segmentation
    Parameters for Limb Movement Prediction Using a Feedforward Neural Network.” <i>Mathematics</i>,
    vol. 10, no. 6, 932, MDPI AG, 2022, doi:<a href="https://doi.org/10.3390/math10060932">10.3390/math10060932</a>.
  short: D. Leserri, N. Grimmelsmann, M. Mechtenberg, H.G. Meyer, A. Schneider, Mathematics
    10 (2022).
date_created: 2022-03-15T19:14:22Z
date_updated: 2026-03-17T15:28:24Z
doi: 10.3390/math10060932
intvolume: '        10'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.3390/math10060932
oa: '1'
project:
- _id: edf53067-b368-11ed-bde2-9f34a4102af5
  name: TransCareTech - Transformation in Care & Technology
- _id: 72dfeb62-b436-11ed-9513-f39505d26204
  name: CareTech OWL - Zentrum für Gesundheit, Soziales und Technologie
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
publication: Mathematics
publication_identifier:
  eissn:
  - 2227-7390
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: Evaluation of sEMG Signal Features and Segmentation Parameters for Limb Movement
  Prediction Using a Feedforward Neural Network
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: '245590'
volume: 10
year: '2022'
...
---
_id: '3717'
alternative_id:
- '1477'
article_number: '2479'
author:
- first_name: Tim
  full_name: Voigt, Tim
  id: '220691'
  last_name: Voigt
- first_name: Martin
  full_name: Kohlhase, Martin
  id: '226669'
  last_name: Kohlhase
  orcid: 0009-0002-9374-0720
- first_name: Oliver
  full_name: Nelles, Oliver
  last_name: Nelles
citation:
  alphadin: '<span style="font-variant:small-caps;">Voigt, Tim</span> ; <span style="font-variant:small-caps;">Kohlhase,
    Martin</span> ; <span style="font-variant:small-caps;">Nelles, Oliver</span>:
    Incremental DoE and Modeling Methodology with Gaussian Process Regression: An
    Industrially Applicable Approach to Incorporate Expert Knowledge. In: <i>Mathematics</i>
    Bd. 9, MDPI AG (2021), Nr. 19'
  ama: 'Voigt T, Kohlhase M, Nelles O. Incremental DoE and Modeling Methodology with
    Gaussian Process Regression: An Industrially Applicable Approach to Incorporate
    Expert Knowledge. <i>Mathematics</i>. 2021;9(19). doi:<a href="https://doi.org/10.3390/math9192479">10.3390/math9192479</a>'
  apa: 'Voigt, T., Kohlhase, M., &#38; Nelles, O. (2021). Incremental DoE and Modeling
    Methodology with Gaussian Process Regression: An Industrially Applicable Approach
    to Incorporate Expert Knowledge. <i>Mathematics</i>, <i>9</i>(19). <a href="https://doi.org/10.3390/math9192479">https://doi.org/10.3390/math9192479</a>'
  bibtex: '@article{Voigt_Kohlhase_Nelles_2021, title={Incremental DoE and Modeling
    Methodology with Gaussian Process Regression: An Industrially Applicable Approach
    to Incorporate Expert Knowledge}, volume={9}, DOI={<a href="https://doi.org/10.3390/math9192479">10.3390/math9192479</a>},
    number={192479}, journal={Mathematics}, publisher={MDPI AG}, author={Voigt, Tim
    and Kohlhase, Martin and Nelles, Oliver}, year={2021} }'
  chicago: 'Voigt, Tim, Martin Kohlhase, and Oliver Nelles. “Incremental DoE and Modeling
    Methodology with Gaussian Process Regression: An Industrially Applicable Approach
    to Incorporate Expert Knowledge.” <i>Mathematics</i> 9, no. 19 (2021). <a href="https://doi.org/10.3390/math9192479">https://doi.org/10.3390/math9192479</a>.'
  ieee: 'T. Voigt, M. Kohlhase, and O. Nelles, “Incremental DoE and Modeling Methodology
    with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate
    Expert Knowledge,” <i>Mathematics</i>, vol. 9, no. 19, 2021.'
  mla: 'Voigt, Tim, et al. “Incremental DoE and Modeling Methodology with Gaussian
    Process Regression: An Industrially Applicable Approach to Incorporate Expert
    Knowledge.” <i>Mathematics</i>, vol. 9, no. 19, 2479, MDPI AG, 2021, doi:<a href="https://doi.org/10.3390/math9192479">10.3390/math9192479</a>.'
  short: T. Voigt, M. Kohlhase, O. Nelles, Mathematics 9 (2021).
date_created: 2023-11-14T10:52:17Z
date_updated: 2026-03-17T15:28:49Z
doi: 10.3390/math9192479
intvolume: '         9'
issue: '19'
keyword:
- Gaussian process regression
- design of experiments
- static process models
- industrial processes
- stepwise experimental design
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/2227-7390/9/19/2479
oa: '1'
publication: Mathematics
publication_identifier:
  eissn:
  - 2227-7390
publication_status: published
publisher: MDPI AG
status: public
title: 'Incremental DoE and Modeling Methodology with Gaussian Process Regression:
  An Industrially Applicable Approach to Incorporate Expert Knowledge'
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: '220548'
volume: 9
year: '2021'
...