Effective partitioning of input domains for ALM algorithm

Afrakoti, I. E. P ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1109/PRIA.2013.6528437
  3. Publisher: 2013
  4. Abstract:
  5. This paper presents a new and simple algorithm for partitioning the input domain for implementation of Active Learning Method (ALM) algorithm. ALM is a pattern-based algorithm for soft computing which uses the Ink Drop Spread (IDS) algorithm as its main engine for feature extraction. In this paper a simple algorithm is introduced with a few computation cost. In order to evaluate the performance of the proposed algorithm, it is applied to two applications, system modeling and pattern recognition. Simulation results show the effectiveness of our algorithm in specifying the appropriate points for dividing the inputs domains
  6. Keywords:
  7. Active learning method (ALM) ; Fuzzy inference algorithm ; Ink drop spread (IDS) ; Active learning methods ; Computation costs ; Fuzzy inference algorithms ; Ink drop spreads ; Main engines ; SIMPLE algorithm ; System modeling ; Drops ; Feature extraction ; Image analysis ; Learning systems ; Soft computing ; Algorithms
  8. Source: 1st Iranian Conference on Pattern Recognition and Image Analysis ; 2013 ; 9781467362047 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6528437