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

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, 1...

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Vydáno v:Water resources management Ročník 32; číslo 4; s. 1325 - 1342
Hlavní autoři: Liu, Dong, Liu, Chunlei, Fu, Qiang, Li, Tianxiao, Khan, Muhammad Imran, Cui, Song, Faiz, Muhammad Abrar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer Netherlands 01.03.2018
Springer Nature B.V
Témata:
Agrochemicals
Algorithms
Ammonia
ammonium nitrogen
Atmospheric Sciences
Capacity
Chemical fertilizers
chickens
China
Civil Engineering
Drinking water
Earth and Environmental Science
Earth Sciences
Environment
Environmental factors
Environmental quality
Evaluation
Farms
Fertilizer application
Fertilizers
fluorides
Genetic algorithms
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrology/Water Resources
Marine environment
Mathematical models
Nitrogen
nitrogen fertilizers
Optimization
Optimization algorithms
Phosphates
phosphorus fertilizers
pollution
Projection
Regional analysis
Surface water
swarms
Water pollution
Water quality
China
Projection pursuit evaluation
Water environmental quality
Algorithm performance
Improved chicken swarm optimization algorithm
ISSN:0920-4741, 1573-1650
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Shrnutí: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 COD Mn , NH 3 -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 NH 3 -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.
Bibliografie:ObjectType-Article-1
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-017-1872-6