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Journal of Applied Sciences
  Year: 2014 | Volume: 14 | Issue: 2 | Page No.: 129-136
DOI: 10.3923/jas.2014.129.136
 
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A Logistical Model Based on the Hamming Competitive Neural Network Algorithm

H. Yongsheng, Du HuaMei and Tang Zhongbin

Abstract:
Based on the Internet of Things, the achieving of the dynamical information about the logistical network becomes a practical matter. With enough information utilizable, the deeply optimization of the logistical service is more possible. In this study, the static and dynamic information of the logistical network for goods dispatching is reformatted. Integrated with the particle swarm optimization algorithm, an optimization model utilizing the algorithm of the Hamming competitive neural network is proposed. In the logistical model, the particle swarm algorithm is used to implement the optimization to the logistical services based on the complex logistical network. In order to reduce the time cost of the particle swarm algorithm, the hamming neural network algorithm is put forward to involve the iteration procedure. Simulative experiments demonstrate that the proposed model can not only reduce the time cost of the optimization procedure but also is effective to achieve optimized service scheme.
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How to cite this article:

H. Yongsheng, Du HuaMei and Tang Zhongbin , 2014. A Logistical Model Based on the Hamming Competitive Neural Network Algorithm. Journal of Applied Sciences, 14: 129-136.

DOI: 10.3923/jas.2014.129.136

URL: https://scialert.net/abstract/?doi=jas.2014.129.136

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