LEADER 03587nam 22005655 450 001 9910548170203321 005 20251223190405.0 010 $a9783658359997$b(electronic bk.) 010 $z9783658359980 024 7 $a10.1007/978-3-658-35999-7 035 $a(MiAaPQ)EBC6896990 035 $a(Au-PeEL)EBL6896990 035 $a(CKB)21325689800041 035 $a(PPN)260830097 035 $a(BIP)83380943 035 $a(BIP)81838962 035 $a(DE-He213)978-3-658-35999-7 035 $a(EXLCZ)9921325689800041 100 $a20220225d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aConstruction of a Concept of Neuronal Modeling /$fby Marcus Grum 205 $a1st ed. 2022. 210 1$aWiesbaden :$cSpringer Fachmedien Wiesbaden :$cImprint: Springer Gabler,$d2022. 215 $a1 online resource (896 pages) 225 1 $aGabler Theses,$x2731-3239 311 08$aPrint version: Grum, Marcus Construction of a Concept of Neuronal Modeling Wiesbaden : Springer Fachmedien Wiesbaden GmbH,c2022 9783658359980 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Problem Analysis and Problem Statement -- Objectives and Methodology -- Design -- Implementation -- Demonstration -- Evaluation -- Concluding Remark. 330 $aThe business problem of having inefficient processes, imprecise process analyses and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS) and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes. About the author Dr.-Ing. Marcus Grum conducts research on neural networks and knowledge processing. The explainable and ethically justifiable integration of artificial intelligence into economic contexts is a major challenge and the subject of his research. He has worked on numerous research and customer projects in the areas of knowledge management, business process management, and artificial intelligence. He graduated from the studies of computer science as well as economics at the University of Potsdam, the Technical University of Berlin and the Humboldt University of Berlin. 410 0$aGabler Theses,$x2731-3239 606 $aBusiness information services 606 $aTechnological innovations 606 $aIT in Business 606 $aInnovation and Technology Management 615 0$aBusiness information services. 615 0$aTechnological innovations. 615 14$aIT in Business. 615 24$aInnovation and Technology Management. 676 $a006.32 700 $aGrum$b Marcus$01208820 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910548170203321 996 $aConstruction of a Concept of Neuronal Modeling$92789026 997 $aUNINA