Multi-agent System for Forecasting Based on Modified Algorithms of Swarm Intelligence and Immune Network Modeling

  • Galina A. SamigulinaEmail author
  • Zhazira A. Massimkanova
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 96)


The use of modern achievements of artificial intelligence in the creation of innovative information forecasting technologies is an urgent task. The article is devoted to the development of multi-agent system for forecasting based on modified algorithms of swarm intelligence and artificial immune systems approach. The construction of an optimal immune network model is one of the most important tasks at solving the problem of image recognition and prediction based on artificial immune systems. The problem of preliminary processing and selection of informative descriptors is solved on the basis of swarm intelligence algorithms. Selection of informative descriptors is carried out based on a multi-algorithmic approach, which allows to choose the algorithm of swarm intelligence, in which the generalization error will be minimal after immune network modeling. An algorithm of functioning of the multi-agent system for forecasting has been developed and a description of the main agents has been given. The modeling results have been presented and a comparative analysis for various algorithms of swarm intelligence has been performed.


Multi-agent system Swarm intelligence Immune network modeling 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Galina A. Samigulina
    • 1
    Email author
  • Zhazira A. Massimkanova
    • 1
  1. 1.Institute of Information and Computational TechnologiesAlmatyKazakhstan

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