摘要
文章利用H-P滤波法分析了山东省海参养殖资源的开发历程,并建立多变量灰色模型MGM(1,n)预测了山东省"十三五期间"的海参养殖产量。预测结果表明,山东省的海参养殖业在"十三五"期间将整体转向生产萎缩阶段,全省海参养殖业发展面临严峻挑战。为了确保山东省海参养殖业的持续高效发展,未来实践中应切实保障海参养殖空间,科学规划海参养殖空间布局,提升海参养殖科技支撑能力,推广生态健康型海参养殖模式,加强海参养殖技能培训和技术推广,同时做大做强海参消费市场,加强海参养殖业行政执法能力建设,并建立健全海参养殖业保险机制。
This paper used the H P filter method to analyze the developing history of sea cucumber aq uaculture and established the multivariable grey model of MGM(1 ,n) to predict the yield of sea cucumber aquaculture in Shandong province.The prediction results showed that the sea cucumber aquaculture in Shandong province will shift to the phase of production shrink in the "13th Five Year Plan" period,and the development of the sea cucumber aquaculture in Shandong province will be faced with severe challenges. In order to ensure the sustainable and efficient development of the sea cucumber aquaculture in Shandong province,it is necessary to effectively protect the sea cucumber breeding space, scientifically plan the spatial layout of sea cucumber aquaculture, en hance scientific and technological supporting capacity of sea cucumber breeding,promote the eco healthy breeding mode of sea cucumber,strengthen the training and technology promotion of sea cucumber breeding,fully tap the demand potential of sea cucumbers, enlarge and strengthen the sea cucumber consumption market, strengthen the administration and law enforcement capacity of the sea cucumber aquaculture,establish and improve the insurance mechanism for the sea cucum bet aquaculture in practice.
作者
卢昆
刘慧迪
包利民
孙吉亭
LU Kun;LIU Huidi;BAO Limin;SUN Jiting(Management College,Ocean University of China,Qingdao 266100,China;Beijing Vocational College of Agriculture,Beijing 100093,China;Shandong Institute of Marine Economy and Culture,Qingdao 266100,China)
出处
《海洋开发与管理》
2018年第7期94-100,共7页
Ocean Development and Management
基金
山东省现代农业产业技术体系创新团队项目(SDAIT-22-09)
中国海洋大学管理学院青年英才支持计划的阶段性研究成果
关键词
海参资源
海参养殖业
海参产业发展
H-P滤波分析
灰色预测
Sea cucumber resources
Sea cucumber aquaculture
Sea cucumber industry development
H- P filter analysis
Gray forecasting model