@article{1444813,
      recid = {1444813},
      author = {Grum, Marcus,},
      title = {Construction of a concept of neuronal modeling /},
      pages = {1 online resource (lv, 848 pages) :},
      abstract = {The 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.},
      url = {http://library.usi.edu/record/1444813},
      doi = {https://doi.org/10.1007/978-3-658-35999-7},
}