scholarly journals Evaluation of water resources system vulnerability based on co-operative co-evolutionary genetic algorithm and projection pursuit model under the DPSIR framework

Author(s):  
Y Zhao ◽  
X H Su ◽  
M H Wang ◽  
Z Y Li ◽  
E K Li ◽  
...  
Author(s):  
Dan Zhao ◽  
Dong Liu ◽  
Qiumei Wang ◽  
Qiuyuan Li ◽  
Xu Liang

Abstract A Projection Pursuit Classification model optimized by the Cat Swarm Optimization algorithm (CSO-PPC) was proposed to evaluate system resilience in Hongxinglong Administration of Heilongjiang Province, China. Meanwhile, the driving forces behind resilience were analyzed using Principal Component Analysis (PCA). CSO-PPC was used to evaluate resilience for the 12 farms in Hongxinglong Administration, and PCA was applied to select the key factors driving their resilience. Results showed that the key factors were per capita water, unit area grain yield, application of fertilizer per unit cultivated area and the proportion of cultivated land, which were closely related to human production and planting area. Overall water resources system resilience improved by 2011 compared to 2005. Specifically, water resources system resilience grades for the 12 farms were divided into five levels from inferior to superior, i.e. I to V. After six years of development, the resilience of eight farms had improved. Farm Youyi and Farm 853 were upgraded from inferior level II to the best level V. However, according to the data, four farms still had low resilience that had not improved in recent years. Further results showed that the driving forces decreased from 1998 to 2003 and increased from 2003 to 2011.


2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chen Hongli ◽  
Wu Yanyan ◽  
Liu Xiuli ◽  
Zhang Wenju

Scientific evaluation of the competitiveness of China’s dairy industry is of great significance to the development of regional dairy industry. In view of the fact that the existing evaluation model cannot solve the dynamic nonlinear optimization problem, this paper established a projection pursuit model based on accelerating genetic algorithm and carried on the comprehensive evaluation and dynamic analysis on the competitiveness of dairy industry in China’s 31 provinces and cities (not including Hong Kong, Macao, and Taiwan) from five dimensions, namely, basic factors of production, the industry demand conditions, the enterprise competitiveness and growth force, related and supporting industries, and the natural environmental elements. It was found that firstly, from the perspective of time, the development trend of China’s dairy industry basically shows a positive trend. With the improvement of national living standards, the competitiveness of the dairy industry is also constantly improved. Secondly, from the perspective of space, regional differences in the competitiveness of the dairy industry are significant. Inner Mongolia, Heilongjiang, Shandong, and Hebei are at the forefront of the development of the industry, while the development of the dairy industry in the rest of the region has a big gap with those areas. From the perspective of regional layout, the advantageous region of China’s dairy industry has been preliminarily formed, and the competitive advantage is mainly concentrated in the northern region. Accordingly, the countermeasures and suggestions to enhance the competitiveness of China’s dairy industry were put forward.


2002 ◽  
Vol 16 (11) ◽  
pp. 2189-2208 ◽  
Author(s):  
Tarek Merabtene ◽  
Akira Kawamura ◽  
Kenji Jinno ◽  
Jonas Olsson

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