Special Sessions

SS29: Swarm Intelligence in Optimizing Solution for Real-World Problems


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Swarm intelligence is the area that revolves around bio-inspired based computation. In the digital world data generated across the world grows exponentially. Processing of the raw data is required for deciding on this fast-growing technology. As mentioned about the big data, the number of attributes describing about the data also increases. Feature selection is a vital task in the machine learning perspective. The Swarm intelligence concept is being used extensively. Classification, clustering, association rule mining, regression, and other algorithms used for modeling the real-world problem for prediction, grouping, decision making, forecasting highly relies on the features. The performance of the system is highly required criteria that depend on the built model. Often smarm intelligence perspective evolved around the lifestyle of creatures like the ant, bat, bee, cuckoo, fish, cuckoo, firefly, wolf, birdís, and so on. Animals being in the group ensures the safety from the predators and for wellbeing bypassing the potential information without delay. Similarly, in the system for the flawless, fast processing of the huge data based on the characteristics of swarm intelligence is the evolving area.

Energy is an indispensable input for human activities that offer driving force by which society function. The developing countries, specially, less developed countries are notoriously energy poor. Energy transition and smart grid application around the world is increasing day by day. Machine learning is everywhere throughout the whole growing and harvesting cycle. Smart technologies and renewable energies, have arisen as new scientific fields that use data intense approaches to drive power industries by minimizing environmental impact.


Topics of interest:

We invite original (un-published) research contributions based on the above mentioned theme including following topics but not limited to:


  • A hybrid approach for disease prediction in crops
  • Metaheuristic approach for weather forecast
  • Swarm intelligence approach to detect intrusion detection
  • Swarm intelligence in designing robotics system
  • Cluster routing for wireless network using artificial intelligence
  • Bio-inspired algorithm for the medical-related application
  • Swarm intelligence for the infrared images
  • GPU based parallel application of swarm intelligence
  • The nature-inspired algorithm in telecommunications

  • Organizers

    Dr. S L Aarthy, Vellore Institute of Technology, Vellore, India Contact:aarthy.sl@vit.ac.in., (M) +91-96000-33077
    Dr. R Sujatha, Vellore Institute of Technology, Vellore. Contact: r.sujatha@vit.ac.in, (M) +91-99435-59395.



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