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Projection Pursuit Evaluation Model of Regional Surface Water Environment Based on Improved Chicken Swarm Optimization Algorithm

Author

Listed:
  • Dong Liu

    (Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University
    Northeast Agricultural University)

  • Chunlei Liu

    (Northeast Agricultural University)

  • Qiang Fu

    (Northeast Agricultural University)

  • Tianxiao Li

    (Northeast Agricultural University)

  • Muhammad Imran Khan

    (Northeast Agricultural University)

  • Song Cui

    (Northeast Agricultural University)

  • Muhammad Abrar Faiz

    (Northeast Agricultural University)

Abstract

A Projection Pursuit Evaluation model of surface water environment based on an Improved Chicken Swarm Optimization Algorithm (ICSOA-PPE) is constructed using the ICSOA to optimize the optimal projection direction. Using the Jiansanjiang Administration in Heilongjiang Province, China as an example, 15 subordinate farms were used as an evaluation unit by selecting water quality indexes including CODMn, NH3-N, TP, TN, F− to evaluate the environmental quality of surface water using the ICSOA-PPE model. The results show that the environmental quality of surface water from all farms in this region was generally poor, except for that at the Qinglongshan, Qindeli and Daxing farms. These three farms met the standard for drinking water sources, while the remaining farms failed to reach the standard. By analyzing the relationship between the total amount of chemical fertilizer application per ha, the amount of nitrogen fertilizer application per ha, the amount of phosphate fertilizer application per ha and the environmental quality of the surface water, a conclusion could be reached that the total amount of chemical fertilizer has a substantial effect on water environment. Additionally, the contribution rate of the amount of nitrogen fertilizer application per ha to the organic pollution and the concentration of NH3-N is substantial, and the amount of phosphate fertilizer influences the water environmental quality to some extent. An analysis and comparison of the traversal capacity, the offset capacity and the convergence capacity of the Genetic Algorithm (GA), the Chicken Swarm Optimization Algorithm (CSOA) and ICSOA reveal that ICSOA is the better optimization algorithm, indicating that the ICSOA-PPE model is logical and reliable.

Suggested Citation

  • Dong Liu & Chunlei Liu & Qiang Fu & Tianxiao Li & Muhammad Imran Khan & Song Cui & Muhammad Abrar Faiz, 2018. "Projection Pursuit Evaluation Model of Regional Surface Water Environment Based on Improved Chicken Swarm Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1325-1342, March.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:4:d:10.1007_s11269-017-1872-6
    DOI: 10.1007/s11269-017-1872-6
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    References listed on IDEAS

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    1. Rangan Gupta & Anandamayee Majumdar, 2014. "Reconsidering the welfare cost of inflation in the US: a nonparametric estimation of the nonlinear long-run money-demand equation using projection pursuit regressions," Empirical Economics, Springer, vol. 46(4), pages 1221-1240, June.
    2. Wei Pei & Qiang Fu & Dong Liu & Tian-xiao Li & Kun Cheng, 2016. "Assessing agricultural drought vulnerability in the Sanjiang Plain based on an improved projection pursuit model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 683-701, May.
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    Cited by:

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