Abstract
Zhang, H.N.; Chen, Z.Y., Holguin-Veras, J., 2020. Optimization of evaluation model for ocean logistics enterprises based on sparse neural network. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 575-578. Coconut Creek (Florida), ISSN 0749-0208.For a long time, marine transportation is one of the important modes of goods transportation between countries. The development of marine transportation is the embodiment of a country's foreign trade level and marine economic competitiveness, which reflects its position in marine transportation. However, the degree of opening to the outside world is gradually increasing, and the estimation error in the method of logistics volume estimation is also gradually increasing. Neural network algorithm is used in this paper to upgrade the material flow model. According to the operation principle of port logistics and the principle of neural network algorithm, based on the historical data of material flow, the final logistics volume estimation results are carried out. Compared with the traditional method, the logistics quantity model described in this paper improves the efficiency and reduces the error.
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