中国沿海省份海参养殖业经济区域类型初探及产量预测分析
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摘要
论文首先运用灰色系统理论中关联分析和聚类分析方法,对我国海参养殖业经济评价指标和各沿海省份海参养殖产业的发展区域类型进行分析。随后运用预测模型对2017-2019年我国海参产量进行了预测。关联分析结果显示:各影响因素的大小依次为海参养殖面积(0.8004)>海参养殖产量(0.7903)>海水养殖专业从业人员(0.7479)>海参苗种数量(0.6498)。聚类分析结果显示:我国海参养殖业的发展区域类型大致可划分为三个区域类型,其中属于I类有山东和辽宁,福建、广东、浙江和河北属于II类,江苏属于III类。预测分析结果显示:我国2017-2019年海参养殖产量为29.00×10~4-37.01×10~4吨,产量呈增长趋势,年均增长率为12.97%。
This paper is firstly based on Grey relationship and Grey constellation cluster method of Grey system theory to analyze the economic evaluation index of Chinese sea cucumber aquaculture industry and the regional types of sea cucumber aquaculture industry in coastal provinces. Then the prediction model is used to predict the yield of Chinese sea cucumber during 2017 to 2019. The Grey relationship results indicate that the greatest factor comes from sea cucumber aquaculture areas(0.8004) >sea cucumber aquaculture production(0.7903) >mariculture professional labor(0.7479) >sea cucumber seedling number(0.6498). The Grey constellation cluster results indicate that sea cucumber aquaculture industry economy can be divided into three types. Shandong and Liaoning are class I. Following by Fujian, Guangdong, Zhejiang and Hebei respectively are class II. Finally Jiangsu is class III. The prediction model results show that sea cucumber aquaculture yield is 29.00×10~4-37.01×10~4t during 2017 to 2019, the yield is increasing and the average annual growth rate is 12.97%.
This paper is firstly based on Grey relationship and Grey constellation cluster method of Grey system theory to analyze the economic evaluation index of Chinese sea cucumber aquaculture industry and the regional types of sea cucumber aquaculture industry in coastal provinces. Then the prediction model is used to predict the yield of Chinese sea cucumber during 2017 to 2019. The Grey relationship results indicate that the greatest factor comes from sea cucumber aquaculture areas(0.8004) >sea cucumber aquaculture production(0.7903) >mariculture professional labor(0.7479) >sea cucumber seedling number(0.6498). The Grey constellation cluster results indicate that sea cucumber aquaculture industry economy can be divided into three types. Shandong and Liaoning are class I. Following by Fujian, Guangdong, Zhejiang and Hebei respectively are class II. Finally Jiangsu is class III. The prediction model results show that sea cucumber aquaculture yield is 29.00×10~4-37.01×10~4t during 2017 to 2019, the yield is increasing and the average annual growth rate is 12.97%.
引文
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[2]吴薇薇,付聪.基于灰色聚类理论的我国农林业航空区域化研究[J].武汉理工大学学报,2013,37(5):994-997,1002.
[3]王筱明,王赞.基于星座聚类方法的农村居民点用地整理时序研究[J].湖北农业科学,2014,53(21):5310-5314.
[4]彭道民,王飞,方志华,等.基于灰色理论的浙江省渔业经济区域类型的初探[J].农村经济与科技,2015,26(8):22-24.
[5]王连华.黄河口地区海参养殖常见问题及关键点控制技术探讨[J].中国水产,2013,(2):76-78.
[6]宋显斌,崔桂静,耿帅帅,等.海参池塘养殖中秋季及越冬前管理的重点[J].科学养鱼,2014,(10):46.
[7]吴杨镝,杜萌萌,韩振威.辽宁省池塘海参养殖生产形势变化分析[J].中国水产,2015,(5):18-21.
[8]苏来金,徐仰丽,张井,等.温州地区海参产业现状及发展对策[J].浙江农业科学,2011,(4):943-946.
[9]边陆军,代国庆.我国海参养殖产业可持续发展的制约因素及对策探讨[J].中国水产,2013,(1):60-62.
[10]徐永东,李可闻.我国海参养殖产业现状分析[J].渔业信息与战略,2013,28(2):117-122.
[11]王晓东.东营市海参养殖产业发展存在的问题及对策[J].河北渔业,2014,(3):58,61.
[12]谢素艳,包鹏云.海参养殖产业持续健康发展的途径[J].水产养殖,2014,35(24):22-25.
[13]海晖.全球海参渔业及其贸易简介[J].中国水产,2009,(7):75-76.
[14]缪圣赐.FAO关注着世界上的海参资源管理[J].现代渔业信息,2010,25(2):34-35.
[15]初建松,朱玉贵.全球海参捕捞与养殖产量变动趋势研究[J].中国渔业经济,2013,31(3):121-126.
[16]刘思峰,谢乃明,等.灰色系统理论及其应用(第四版)[M].北京:科学出版社,2008.1-224.
[17]陈新军.灰色系统理论在渔业科学中的应用[M].北京:中国农业出版社,2003.1-128.
[18]陈鹏宇.灰色GM(1,1)模型的改进[J].山东理工大学学报,2009,23(6):80-82.