By Gaby Neumann, Juri Tolujew (auth.), Aleksander Byrski, Zuzana Oplatková, Marco Carvalho, Marek Kisiel-Dorohinicki (eds.)
The human means to summary complicated structures and phenomena into simplified types has performed a severe function within the fast evolution of our sleek commercial procedures and scienti c learn. As a technological know-how and an paintings, Modelling and Simulation were one of many center enablers of this amazing human hint, and became an issue of serious value for researchers and practitioners.
This publication was once created to bring together the most contemporary thoughts, advances, demanding situations and concepts linked to clever Modelling and Simulation frameworks, instruments and purposes. The rst bankruptcy discusses the $64000 facets of a human interplay and the proper interpretation of effects in the course of simulations. the second one bankruptcy will get to the center of the research of entrepreneurship by way of agent-based modelling and simulations.
The following 3 chapters assemble the valuable topic of simulation frameworks, rst describing an agent-based simulation framework, then a simulator for electric machines, and nally an airborne community emulation surroundings. the 2 next chapters speak about strength distribution networks from assorted issues of view|anticipation and optimization of multi-echelon stock coverage. After that, the publication comprises additionally a bunch of chapters discussing the mathematical modelling supported via veri cation simulations, and a suite of chapters with types synthesised through arti cial intelligence instruments and complicated automata framework. finally, the booklet incorporates a bankruptcy introducing using graph-grammar version for iteration of threedimensional computational meshes and a bankruptcy keen on the experimental and computational effects relating to simulation of aero engine vortexes. Authors think, that this ebook is a precious connection with researchers and practitioners within the eld, in addition to an idea to these attracted to the world of clever Modelling and Simulation.
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Extra info for Advances in Intelligent Modelling and Simulation: Simulation Tools and Applications
In: Proc. Winter Simulation Conference, pp. 829–839 (2000) 4. : The current state of knowledge management. In: Liebowitz, J. ) Knowledge Management Handbook. CRC Press, Boca Raton (1999) 5. : Enhacing modelling and simulation accreditation by structuring verification and validation results. In: Proc. Winter Simulation Conference, pp. 840–848 (2000) Requirements and Solutions for a More Knowledgeable User-Model Dialogue 25 6. : Ein fallbasierter ansatz für die computergestützte nutzung von erfahrungswissen bei der projektarbeit (a case-based approach for computer-based use of experience-based knowledge in projects).
Simulation experts and domain experts, need to be encouraged (and supported) permanently to provide background knowledge about his or her motivation for: • • • • going in one rather than the other direction; changing the model structure or parameters in a certain way; keeping a particular type of possible solution and abandoning others; looking for information, knowledge and support from one source instead of another. This helps to identify (i) who knows what about the object of investigation, but also about the simulation project behind it, (ii) why something was decided in which way, (iii) which system configuration and which set of parameters worked how well together, (iv) what is represented in the simulation model, and (v) what are the limitations of its validity and usability.
In  authors assume that simulation usually aims to specify whether or not the concept of a material flow system meets formal requirements, but not how well it does it. This is said to be caused in limited methodological support and therefore strongly depend on the modelling/planning expert’s experience and expertise. This is to be overcome by eliminating the user as weakest point through automatic analysis. For this an analysis tool is proposed that helps in identifying the concept’s or the system’s weak points, specifying their primary reasons and pointing out system immanent potential for performance increase.