Exploring metaheuristics in a ssFCM Clustering Framework

By Dr. Daphne Lai

EXPLORING METAHEURISTICS IN A SEMISUPERVISED FUZZY C-MEANS (ssFCM) CLUSTERING FRAMEWORK

  • Aims : An intelligent system is required to select the most suitable techniques for automation of processes within the ssFCM framework.
  • Duration: 4 yrs [2015-2018] (Extend to Evo Comp)
  • Source and Amount of Funding: UBD, BND 9,231
  • Collaborator’s Name: Prof Jon Garibaldi, U. Nottingham, UK; Prof Yuji Sato, Hosei U., Japan, Prof Eran Edirisinghe, Loughborough U, UK;
  • Number of Publications – 3 conference papers, 1 journal paper (IMF 2019: 3.050)
  • Link: [RG Project link]