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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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| Hao, Chun-xu; Yang, Li-fei; Wen, Ya-li. |
| According to the data of economic development in Beijing from the year 1995 to 2007, relevant economic indices are selected to analyze the economic development level of Beijing by the Principal Component Analysis Method. Result shows that the national economy maintains high, sustainable and stable development in the years 1995-2007. Both the primary and secondary industry output values have increased year by year; and the tertiary industry output value has grown rapidly. The annual gross domestic product, the output value of tertiary industry, and the total retail sales of consumer goods have the greatest impact on economic level of Beijing. Output value of secondary industry is the growth ability factor in economic environment. Empirical analysis shows... |
| Tipo: Journal Article |
Palavras-chave: Economic level; Principal component analysis; SPSS statistical software; China; Agribusiness. |
| Ano: 2009 |
URL: http://purl.umn.edu/93459 |
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