欢迎访问林草资源研究

Forest and Grassland Resources Research >

2017 , Vol. 0 >Issue 5: 114 - 119

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2017.05.019

Technical Application

Grey Analysis Prediction on Forestry Industrial Structure in Fujian

  • Ludong XU ,
  • Fuhui LIU ,
  • Chaofa HUANG ,
  • Xiaochun SHI ,
  • Yangxin CAI ,
  • Xinwang CHEN ,
  • Dexiang ZHENG
Expand
  • 1. Forestry College,Fujian Agriculture and Forestry University,Fuzhou 350002,China
    2. Fujian Forestry Survey and Planning Institute,Fuzhou 350003,China

Received date: 2017-07-12

  Revised date: 2017-09-28

  Online published: 2020-09-24

Fold

Abstract

Based on the forestry statistical data of Fujian Province in 2005—2015,the gray correlation analysis method was used to calculate the correlation degree of three forestry output values and the total forestry output value in Fujian Province,and then the current situation and dynamic changes of the Fujian forestry industrial structure were analyzed.The prediction model of GM(1,1) grey was established to forecast and analyse the changes of Fujian Province three forestry output values and the total forestry output value.The results show that the grey correlation degrees of Fujian Province three forestry output values and the total forestry output value in 2005—2015 were 0.8564,0.9415,0.7654,respectively.And a forestry industrial structure pattern would be formed in which the second industry is the leading factor,followed by the first and third industries.In the next ten years,with the rapid improvement and development of living standards and the third industry,the value will be more than the first industry,forming a new pattern of “two,three and one” industrial structure with the second industry as the leading one and the first and third industries developing steadily.

Key words： Fujian Province; forestry industry; grey correlation; GM(1,1)model; industrial structure

Cite this article

Ludong XU , Fuhui LIU , Chaofa HUANG , Xiaochun SHI , Yangxin CAI , Xinwang CHEN , Dexiang ZHENG . Grey Analysis Prediction on Forestry Industrial Structure in Fujian[J]. Forest and Grassland Resources Research, 2017 , 0(5) : 114 -119 . DOI: 10.13466/j.cnki.lyzygl.2017.05.019

References

[1] 施晓春, 黄朝法, 陈信旺, 等. 闽台森林经营与施策对比分析[J].林业勘察设计, 2017(1):1-6.
[2] Yao Shunbo, Wang Bowen, Liu Cang, et al. Research on Institutional Innovation of Non-public Forestry[J]. 生态经济:英文版, 2005,1(4):87-91.
[3] 李鹏源. 福建省林业产业可持续发展[J].北京农业, 2013(27):69-70.
[4] 邵砾群, 陈海滨, 刘军弟, 等. 基于灰色理论的陕西省林业产业结构分析预测[J]. 西北林学院学报, 2012,27(5):289-292.
[5] 尹少华, 姜微, 张慧军. 基于灰色系统理论的湖南林业产业结构预测研究[J]. 林业经济问题, 2008,28(4):302-305.
[6] 朱玉杰, 高晓雨. 黑龙江省林业产业结构的关联分析和灰色预测[J]. 森林工程, 2008,24(6):77-80.
[7] 朱曼, 苏喜友. 基于GM(1,1)模型的四川省林业产业结构预测[J]. 四川农业大学学报, 2013,31(1):105-109.
[8] 冯洁. 福建林业产业发展对策研究[J].金融经济, 2012(4):20-21.
[9] 伍清亮. 福建省林业产业可持续发展研究[D]. 福州:福建农林大学, 2011, 15-20.
[10] 杨云. 福建省林业产业结构研究[D]. 福州:福建农林大学, 2005, 12-15.
[11] 王林琳, 翟印礼. 基于灰色理论的辽宁林业产业结构分析[J]. 森林工程, 2008,24(4):85-89.
[12] 王桂涛, 胡申, 温亚利. 中国林业产业结构灰色预测分析[J]. 安徽农业科学, 2011,39(10):6215-6217.
[13] 尚旭东, 宋国宇. 基于灰色关联分析的河北省林业产业结构研究[J].北方园艺, 2011(2):212-216.
[14] 李元元, 聂华. 北京市林业产业结构发展的灰色动态关联分析[J]. 林业调查规划, 2006,31(3):94-97.
[15] 赵金环, 陈建强, 郭立智. Excel在动态GM(1,1)模型预测及检验中的应用[J]. 青岛理工大学学报, 2007,28(4):69-73.
[16] 杜昕, 李钢铁, 马骏骥. 基于GM(1,1)模型群内蒙古森林资源的动态预测[J]. 内蒙古林业科技, 2015,41(1):17-22.
[17] 林筱文, 徐丽, 赵彬, 等. 基于灰色关联模型的福建海洋产业分析[J].发展研究, 2011(1):73-77.
[18] 康彦彦, 尚丽香. 基于灰色关联理论的资源型城市产业分析[J]. 山东师范大学学报:人文社会科学版, 2011,56(2):148-152.
Options
Outlines

/

〈 〉