摘要
研究借鉴有关区域承载力的理论和方法,构建了海域承载力评价指标体系,采用多维状态空间法对海域理想状态承载力以及现实的承载状况进行了定量研究;建立了基于BP神经网络的海域承载状况仿真预警模型,结合情景分析法对山东海域承载状况进行了仿真预警。研究结果表明:山东省海域1996-2010年处于超载状态,但其承载状况逐年好转;在资源环境子、经济和社会子系统处于"高发展"情景下,2015年山东海域将达到弱可持续发展状态;BP神经网络用于海域承载状况的仿真预警具有较高的精确度。
Based on the theories and methods of regional carrying capacity, the carrying capacity evaluation index system of sea area is built in this paper, using multi-dimensional state space method for the carrying capacity quantitative research. In view of the powerful learning ability of fitting, the simulation warning model is established for sea area carrying conditions based on the BP neural network. In this paper, the sea area carrying state in Shandong Province is evaluated. And with the scenario analysis, we have made the simulation and early-warning of the sea area in Shandong Province. The results showed that： the carrying state of sea area in Shandong Province was in the overloaded condition from 1996 to 2010.But its carrying condition was gradually improved year by year and the sea area would reach the state of weak sustainable development in the high development of environmental, economic and social subsystem in 2015. Also it can be concluded that the method of using BP neural network in the simulation warning of the carrying capacity of the sea area has a high degree of accuracy.
出处
《海洋通报》
CAS
CSCD
北大核心
2015年第6期608-615,共8页
Marine Science Bulletin
基金
国家自然科学基金(41571127
41201114)
辽宁省高等学校优秀科技人才支持计划(WR2014005)
关键词
海域承载力
多维状态空间
BP神经网络
预警
山东省
carrying capacity of sea area
multi-dimensional state space
BP neural network
early-warning
Shandong Province
