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Research on the Concentration Prediction of Nitrogen in Red Tide Based on an Optimal Grey Verhulst Model

Author

Listed:
  • Xiaomei Hu
  • Yubin Wang
  • Yue Yu
  • Dong Wang
  • Yuan Tian

Abstract

In order to reduce the harm of red tide to marine ecological balance, marine fisheries, aquatic resources, and human health, an optimal Grey Verhulst model is proposed to predict the concentration of nitrogen in seawater, which is the key factor in red tide. The Grey Verhulst model is established according to the existing concentration data series of nitrogen in seawater, which is then optimized based on background value and time response formula to predict the future changes in the nitrogen concentration in seawater. Finally, the accuracy of the model is tested by the posterior test. The results show that the prediction value based on the optimal Grey Verhulst model is in good agreement with the measured nitrogen concentration in seawater, which proves the effectiveness of the optimal Grey Verhulst model in the forecast of red tide.

Suggested Citation

  • Xiaomei Hu & Yubin Wang & Yue Yu & Dong Wang & Yuan Tian, 2016. "Research on the Concentration Prediction of Nitrogen in Red Tide Based on an Optimal Grey Verhulst Model," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-9, September.
    • Handle: RePEc:hin:jnlmpe:9786107
    DOI: 10.1155/2016/9786107
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    Cited by:

    1. Tingting Wang & Zhuolin Li & Xiulin Geng & Baogang Jin & Lingyu Xu, 2022. "Time Series Prediction of Sea Surface Temperature Based on an Adaptive Graph Learning Neural Model," Future Internet, MDPI, vol. 14(6), pages 1-13, May.

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