Pattern recognition with neural networks combined by genetic algorithm

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60 Citations (Scopus)


Soft computing techniques have been recently exploited as a promising tool for achieving high performance in pattern recognition. This paper presents a hybrid method which combines neural network classifiers by genetic algorithm. Genetic algorithm gives us an effective vehicle to determine the optimal weight parameters that are multiplied by the network outputs as coefficients. The experimental results with the recognition problem of totally unconstrained handwritten numerals show that the genetic algorithm produces better results than the conventional methods such as averaging and Borda count.

Original languageEnglish
Pages (from-to)339-347
Number of pages9
JournalFuzzy Sets and Systems
Issue number2
Publication statusPublished - 1999 Apr 16

All Science Journal Classification (ASJC) codes

  • Logic
  • Artificial Intelligence


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