Apple surface defect detection research based on improved particle swarm optimization algorithm
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(Mechanical and Energy Engineering, Huang Huai University, Zhumadian, Henan 463000, China)

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    Abstract:

    Premature judgment mechanism of particle swarm is established with fitness function. Adaptive adjustment of particle inertia weigh and acceleration factor of anti cosine strategy are optimized particle swarm to give the apple surface defect process. Simulation results show that improved particle swarm algorithm is more clearer detecting the defect of apple surface, the maximum missing rate test index is 4.5%, and less than other algorithms, and the least time comsuming in complete the missing rate, so that it is the new method for quality detection of apple.

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程磊.基于改进粒子群算法的苹果表面缺陷检测[J].食品与机械英文版,2018,34(3):141-145.

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History
  • Received:July 08,2017
  • Revised:
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  • Online: March 17,2023
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