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Aims and Scope

Modelling and Simulation in Engineering aims at providing a forum for the discussion of formalisms, methodologies and simulation tools that are intended to support the new, broader interpretation of Engineering. Competitive pressures of Global Economy have had a profound effect on the manufacturing in Europe, Japan and the USA with much of the production being outsourced. In this context the traditional interpretation of engineering profession linked to the actual manufacturing needs to be broadened to include the integration of outsourced components and the consideration of logistic, economical and human factors in the design of engineering products and services.

Modelling and Simulation in Engineering intends to report leading-edge scientific contributions from mathematics, computer science, various sub-disciplines of engineering, management, psychology and cross-cultural communication, all of which focus on the modelling and simulation of human-centred engineering systems.

Subject areas of Modelling and Simulation in Engineering include (but are not limited to):

  • Mathematical formalisms of system modelling
    • Analytical
    • Stochastic
    • Fuzzy
    • Granular
    • Set-membership
  • Simulation methodologies and tools
    • Continuous simulation
    • Discrete and combined simulation
    • Stochastic simulations
    • Game and fuzzy game theory
    • Finite automata
    • Simulation modelling
    • Optimisation, verification and testing
    • Agent-based simulation
  • Knowledge and culture mining/processing
    • Computation with information described in NL
    • Ontologies and knowledge modelling
    • Model morphisms
    • NL discourse analysis
  • Complex systems modelling
    • Qualitative modelling
    • Multi-resolution modelling and simulation
    • Modelling abstractions
    • Numerical methods, algorithms and simulations
  • Computational Intelligence
    • Neural networks
    • Fuzzy logic
    • Evolutionary techniques
    • Soft computing for human interaction
    • Ambient intelligence and ubiquitous computing
    • Symbolic processing
  • Simulation Visualisation
    • Visualisation algorithms
    • Virtual and augmented reality
    • Virtual prototyping
    • Tools and systems for visualisation
  • Frontiers in HCMS
    • Computational and physical limitations
  • Applications
    • Interoperability of systems and applications
    • Case studies and best practices
    • Socio-technical simulation (logistics, transportation, etc.)