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Academic Journal of Environment & Earth Science, 2020, 2(1); doi: 10.25236/AJEE.2020.020101.

The Migration Coefficient Prediction Based on BP Neural Network


Yumeng Qi, Yanbing Chen

Corresponding Author:
Yumeng Qi

School of economics and management, Northeast Forestry University, Harbin, Heilongjiang, 150040, China


Changes in ocean temperature will greatly affect the survival of marine life. Herring and mackerel, which are important sources of the Scottish fisheries economy, migrate as seawater temperatures rise. As consultants to the Scottish North Atlantic Fisheries Management Association, we need to investigate the migration of these two fish. In this paper, we first found out the concentrated factors that may affect fish migration, and processed them through principal component analysis. And then through BP neural network we predict the migration coefficient and scaling ratio, and finally uses ARCGIS software to draw the migration trajectory of the two fish species over the next 50 years and concluded that the school of fish should migrate northward beyond Norway.


BP neural network, Migration coefficient

Cite This Paper

Yumeng Qi, Yanbing Chen. The Migration Coefficient Prediction Based on BP Neural Network. Academic Journal of Environment & Earth Science (2020) Vol. 2 Issue 1: 1-5. https://doi.org/10.25236/AJEE.2020.020101.


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