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| Men, Ke-pei; Zhao, Kai. |
| In order to analyze the relation between agricultural input factors and economic growth in Anhui Province, the evaluation index system of agricultural input is built from the perspectives of subject, object and tools based on grey system theory. The government investment in agricultural science and technology is selected as the index of labor subject, that is labor-related index（X1）, the total sown area of crops is selected as the index of labor object（X2）, the investment in rural water and electricity construction is chosen as the index of tools（X3）, and the GDP of Anhui Province is denoted by X0. According to the relevant data, the improved model of grey correlation analysis is adopted to calculate the correlation among the investment in agricultural... |
| Tipo: Journal Article |
Palavras-chave: Anhui Province; Agricultural input factors; Grey correlation; GDP; China; Agribusiness. |
| Ano: 2010 |
URL: http://purl.umn.edu/93664 |
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| Tao, Ai-xiang. |
| Taking Jiangsu Province for example and using the relevant data in Jiangsu Statistical Yearbook and Statistical Communique of Jiangsu Province on National Economic and Social Development during 2002-2009, the thesis selects eight indexes including per capita net income of farmers, the fixed asset investment level in rural areas, average educational level, agricultural scientific and technological level, urbanization level, industrialization level, average consumption level per rural residents and per capita GDP and adopts the theory of grey correlation to analyze the factors influencing the peasants’ net income. As shown in the result, the effect on the peasants’ net income gives the following subsequence from great to little: average consumption level per... |
| Tipo: Journal Article |
Palavras-chave: Peasant’s income; Grey correlation; Problems concerning agriculture; Rural area and rural people; Per capita net income; China; Agribusiness. |
| Ano: 2010 |
URL: http://purl.umn.edu/96046 |
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| Weng, Gui-tao; Hu, Sheng; Wen, Ya-li. |
| The grey relevance analysis is applied to study the 1996-2009 output value structure of china forestry system. Based on GM(1,1) model, information model is established to predict the forestry industrial structure of China in the next 10 years. Result shows that grey correlations between the three forestry industries and the forestry output value are 0.849 1, 0.731 1 and 0.821 3, respectively, with its order being secondary industry＜tertiary industry＜primary industry. Prediction result shows that forestry industry of China is in the middle stage of industrialization; and both secondary and tertiary industries will develop rapidly and become the leading industries. |
| Tipo: Journal Article |
Palavras-chave: Forestry industrial structure; Grey correlation; Grey prediction; GM(1，1) model; China; Agribusiness. |
| Ano: 2011 |
URL: http://purl.umn.edu/108401 |
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