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Study on Waste Type Identification Method Based on Bird Flock Neural Network

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  • Shifeng Li
  • Liyu Chen

Abstract

According to the waste type identification requirement in waste classification, a waste type identification method based on a bird flock neural network (BFNN) was proposed. The problem of obtaining the feature dataset of waste images was considered, and color histogram and texture feature extraction techniques were used. The local optimum problem of a typical backpropagation neural network (BPNN) was considered, and a bird flock optimization (BFO) algorithm was proposed. The accuracy problem of the typical BPNN was considered, and a new online weight adjustment method of neurons was proposed. The number of hidden layer neurons (nodes) of the typical BPNN was considered, and an online adjustment method was proposed. The experimental results show that the recyclables (paper, plastic, glass, and cloth) and nonrecyclables can effectively be identified by the waste type identification method based on the BFNN, and the recognition accuracy is 81% which meets actual needs.

Suggested Citation

  • Shifeng Li & Liyu Chen, 2020. "Study on Waste Type Identification Method Based on Bird Flock Neural Network," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, August.
    • Handle: RePEc:hin:jnlmpe:9214350
    DOI: 10.1155/2020/9214350
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