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

Dong Liu, Chunlei Liu, Qiang Fu (), Tianxiao Li, Muhammad Imran Khan, Song Cui and Muhammad Abrar Faiz
Additional contact information
Dong Liu: 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

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 4, No 9, 1325-1342

Abstract: 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.

Keywords: Water environmental quality; Improved chicken swarm optimization algorithm; Projection pursuit evaluation; Algorithm performance (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-017-1872-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:32:y:2018:i:4:d:10.1007_s11269-017-1872-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-017-1872-6

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().