Discrete and Continuous Aspects of Nature Inspired Methods

  • Martin Macaš
  • Miroslav Burša
  • Lenka Lhotská
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)


In nature, industry, medicine, social environment, simply everywhere we find a lot of data that bear certain information. A dictionary defines data as facts or figures from which conclusions may be drawn. Data can be classified as either numeric or nonnumeric. The structure and nature of data greatly affects the choice of analysis method. Under the term structure we understand the facts that the data might be not a single number but n-tuples of measurements. Structure is also very closely linked to the reason of data collection and method of measurement. The paper describes the similarities and differences of nature inspired methods and their natural counterparts in light of continuous and discrete properties. Different examples of nature inspired methods are inspected in terms of data, problem domains and inner structure and principles.


Particle Swarm Optimization Travelling Salesman Problem Discrete Particle Swarm Optimization Discrete Property Real Neuron 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Martin Macaš
    • 1
  • Miroslav Burša
    • 1
  • Lenka Lhotská
    • 1
  1. 1.Gerstner LaboratoryCzech Technical University in PraguePrague 6Czech Republic

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