Design of a neuronal training modeling language
- As the complexity of learning task requirements, computer infrastruc- tures and knowledge acquisition for artificial neuronal networks (ANN) is in- creasing, it is challenging to talk about ANN without creating misunderstandings. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information and knowledge on the base of an integration with knowledge- intensive business process models and a process-oriented knowledge manage- ment are attractive. With the aim of making the design of learning tasks express- ible by models, this paper proposes a graphical modeling language called Neu- ronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaptation exemplifies its use as a first demonstration.
Author details: | Marcus GrumORCiDGND, Werner Hiessl, Karl Maresch, Norbert GronauORCiDGND |
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URL: | https://www.aes-journal.com/index.php/ais-tes/article/view/20/18 |
DOI: | https://doi.org/10.30844/aistes.v5i1.20 |
ISSN: | 1867-7134 |
Title of parent work (English): | AIS-Transactions on enterprise systems |
Subtitle (English): | exemplified with the AI-based dynamic GUI adaption |
Publisher: | GITO-Publ., Verl. für Industrielle Informationstechnik und Organisation |
Place of publishing: | Berlin |
Publication type: | Article |
Language: | English |
Date of first publication: | 2021/03/25 |
Publication year: | 2021 |
Release date: | 2024/04/11 |
Tag: | AI and business informatics; AI-based decision support system; cooperative AI (human-in-the-loop); development of AI-based systems; modeling language; process-oriented knowledge acquisition |
Volume: | 5 |
Issue: | 1 |
Number of pages: | 16 |
Organizational units: | Wirtschafts- und Sozialwissenschaftliche Fakultät / Wirtschaftswissenschaften / Fachgruppe Betriebswirtschaftslehre |
DDC classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Peer review: | Nicht referiert |
Publishing method: | Open Access / Gold Open-Access |