IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v32y2018i4d10.1007_s11269-017-1872-6.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-017-1872-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-017-1872-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qin, Jingxiu & Duan, Weili & Chen, Yaning & Dukhovny, Viktor A. & Sorokin, Denis & Li, Yupeng & Wang, Xuanxuan, 2022. "Comprehensive evaluation and sustainable development of water–energy–food–ecology systems in Central Asia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    2. Wang, Qiang & Zhan, Lina, 2019. "Assessing the sustainability of the shale gas industry by combining DPSIRM model and RAGA-PP techniques: An empirical analysis of Sichuan and Chongqing, China," Energy, Elsevier, vol. 176(C), pages 353-364.
    3. Wei Pei & Lei Hao & Qiang Fu & Yongtai Ren & Tianxiao Li, 2023. "Study on Agricultural Drought Risk Assessment Based on Information Entropy and a Cluster Projection Pursuit Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 619-638, January.
    4. Wang, Xuanxuan & Chen, Yaning & Li, Zhi & Fang, Gonghuan & Wang, Yi, 2020. "Development and utilization of water resources and assessment of water security in Central Asia," Agricultural Water Management, Elsevier, vol. 240(C).
    5. Elena Niculina Dragoi & Vlad Dafinescu, 2021. "Review of Metaheuristics Inspired from the Animal Kingdom," Mathematics, MDPI, vol. 9(18), pages 1-52, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Qiang & Zhan, Lina, 2019. "Assessing the sustainability of the shale gas industry by combining DPSIRM model and RAGA-PP techniques: An empirical analysis of Sichuan and Chongqing, China," Energy, Elsevier, vol. 176(C), pages 353-364.
    2. Abdol Rassoul Zarei & Mohammad Reza Mahmoudi, 2022. "Assessing and Predicting the Vulnerability to Agrometeorological Drought Using the Fuzzy-AHP and Second-order Markov Chain techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4403-4424, September.
    3. Matteo Mogliani & Giovanni Urga, 2018. "On the Instability of Long‐Run Money Demand and the Welfare Cost of Inflation in the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(7), pages 1645-1660, October.
    4. Miller, Stephen M. & Martins, Luis Filipe & Gupta, Rangan, 2019. "A Time-Varying Approach Of The Us Welfare Cost Of Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 775-797, March.
    5. Helmut Herwartz & Jordi Sardà & Bernd Theilen, 2016. "Money demand and the shadow economy: empirical evidence from OECD countries," Empirical Economics, Springer, vol. 50(4), pages 1627-1645, June.
    6. Wei Pei & Qiang Fu & Dong Liu & Tianxiao Li & Kun Cheng & Song Cui, 2019. "A Novel Method for Agricultural Drought Risk Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 2033-2047, April.
    7. Kun Cheng & Qiang Fu & Song Cui & Tian-xiao Li & Wei Pei & Dong Liu & Jun Meng, 2017. "Evaluation of the land carrying capacity of major grain-producing areas and the identification of risk factors," 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. 86(1), pages 263-280, March.
    8. Plakandaras, Vasilios & Gupta, Rangan & Karmakar, Sayar & Wohar, Mark E., 2023. "Are real interest rates a monetary phenomenon? Evidence from 700 years of data," Research in International Business and Finance, Elsevier, vol. 66(C).
    9. Zhuguang Lan & Ming Huang, 2018. "Safety assessment for seawall based on constrained maximum entropy 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. 91(3), pages 1165-1178, April.
    10. repec:ipg:wpaper:2014-474 is not listed on IDEAS
    11. Hongpeng Guo & Jia Chen & Chulin Pan, 2021. "Assessment on Agricultural Drought Vulnerability and Spatial Heterogeneity Study in China," IJERPH, MDPI, vol. 18(9), pages 1-17, April.
    12. Huifang Sun & Yaoguo Dang & Wenxin Mao, 2019. "Identifying key factors of regional agricultural drought vulnerability using a panel data grey combined method," 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. 98(2), pages 621-642, September.
    13. Mohsen Bahmani-Oskooee & Majid Maki-Nayeri, 2018. "Asymmetric Effects of Policy Uncertainty on the Demand for Money in the United States," JRFM, MDPI, vol. 12(1), pages 1-13, December.
    14. Yongsheng Jiang & Dong Zhao & Dedong Wang & Yudong Xing, 2019. "Sustainable Performance of Buildings through Modular Prefabrication in the Construction Phase: A Comparative Study," Sustainability, MDPI, vol. 11(20), pages 1-15, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:32:y:2018:i:4:d:10.1007_s11269-017-1872-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.