Fruit classification by wavelet-entropy and feedforward neural network trained by fitness-scaled chaotic abc and biogeography-based optimization

HIGHLIGHTS

• who: Shuihua Wang and colleagues from the School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu , have published the paper: Fruit Classification by Wavelet-Entropy and Feedforward Neural Network Trained by Fitness-Scaled Chaotic ABC and Biogeography-Based Optimization, in the Journal: Entropy 2015, 17, 5711-5728 of 22/05/2015
• what: The authors proposed two novel machine-learning based classification methods. The authors proposed to use both FSCABC and another rather novel optimization method-biogeography-based optimization (BBO). To make the analysis statistically significant, a five-fold stratified cross validation was employed . . .
  

   

  

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