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2019 | 28 | 2 |

Tytuł artykułu

Simulating land use structure optimization based on an improved multi-objective differential evolution algorithm

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Optimizing land use structure is currently a hot research topic in the land resource management field. In this study, we constructed a new land use structure optimization model based on the improved multi-objective differential evolution algorithm. This model made improvements in two aspects of the classic differential evolution algorithm, i.e., control parameters and adaptive strategies. On this basis, we established a multi-objective function by taking ecological benefits and economic benefits as the objectives. According to the real situation of the study area, we established multiple constraint conditions and finally established an improved multi-objective differential evolution model. By taking the year 2010 as the base period, we simulated an optimized land use quantitative structure in 2020 for the study area and compared this optimized structure with classic linear programming. The experimental results showed that although the annual ecological benefits in the study area decreased by 5,105,300 yuan, the annual economic benefits increased by 69,133,500 yuan, and the annual total benefits increased by 20,878,300 yuan – an increase of 0.44%. This showed that the land use structure obtained by using the optimization model proposed in this paper was more reasonable. The results indicated that the model established in this study possessed quite good properties and could meet the requirements for the regional land use structure optimization under multiple constraint conditions. The optimized results can provide the scientific basis for formulating appropriate measures for regional land resources use.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

28

Numer

2

Opis fizyczny

p.887-889,fig.,ref.

Twórcy

autor
  • School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, China
autor
  • School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, China
autor
  • School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, China

Bibliografia

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  • 16. DHAHRI H., ALIMI A.M., ABRAHAM A. Hierarchical multi-dimensional differential evolution for the design of beta basis function neural network. Neurocomputing. 97, 131, 2012.
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  • 18. HELON V. H. A., LEANDRO d. S. C., VIVIANA C. M., ALIREZA A. An improved free search differential evolution algorithm: A case study on parameters identification of one diode equivalent circuit of a solar cell module. Energy. 93, 1515, 2015.
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  • 22. GUO J., GUI W.H., YANG C.H. An improved hybrid differential evolution algorithm used for multi-objective optimization of aluminum electrolysis. Journal of Central South University (Science and Technology). 4, 184, 2012.
  • 23. WANG S.D. Research on regional land use structure and spatial pattern optimization under ecological constraints. Beijing Normal University, Beijing. 40, 2013.
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  • 25. PARTHA B., SUGANTHANA P.N., MALLIPEDDIB R., GEHAN A. Optimal power flow solutions using differential evolution algorithm integrated with effective constraint handling techniques. Engineering Applications of Artificial Intelligence. 68, 81, 2018.
  • 26. SHILPA S., SHYAM L. Modified differential evolution algorithm for contrast and brightness enhancement of satellite images. Applied Soft Computing. 61, 622, 2017.
  • 27. ZHU B., JIN W.D., YU Z. B. Intrapulse feature evaluation model of radar emitter signal based on differential evolution, particle swarm optimization and projection pursuit algorithm. Journal of Southwest Jiaotong University. 53, 189, 2018.
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Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

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