Approach the Interval Type-2 Fuzzy System and PSO Technique in Landcover Classification

  • Dinh Sinh MaiEmail author
  • Long Thanh Ngo
  • Le Hung Trinh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12034)


In fuzzy classification systems, the estimation of the optimal number of clusters and building base-rules are very important and greatly affects the accuracy of the fuzzy system. Base-rules are often built on the experience of experts, but this is not always good and the results are often unstable. Particle swarm optimization (PSO) techniques have many advantages in finding optimal solutions and have been used successfully in many practical problems. This paper proposes a method using the PSO technique to build base-rules for the interval type-2 fuzzy system (IT2FS). Experiments performed on satellite image data for the landcover classification problem have shown that the proposed method works more stably and effectively than the non-PSO technique.


Type-2 fuzzy set Interval type-2 fuzzy system PSO Fuzzy system Landcover Satellite image 



This research is funded by the Newton Fund, under the NAFOSTED - UK Academies collaboration programme. This work was supported by the Domestic Master/PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF).


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Le Quy Don Technical UniversityHanoiVietnam

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