摘要
依据国有林区特征和低碳循环经济发展评价的独特性,构建了国有林区低碳循环经济耦合发展评价指标体系,并运用径向基神经网络构建了评价模型,以黑龙江省伊春国有林区展开实证研究,结果表明国有林区在很多方面已经有所改善,但在低碳循环技术、低碳排放能耗方面水平较低。总体发展呈缓慢上升中,但基本处于中等偏下水平。有必要进行针对性的调整改造,加大转型力度。
According to state-owned forest characteristics and the evaluation unique of low-carbon cycle economy,this paper builds low-carbon cycle economy coupled development evaluation system and assessment model based on RBF neural network.At this time,this paper carries out empirical research taking Yi chun forest of Heilongjiang province.It shows that state-owned forest has improved in many aspects,but the levels are low in low-carbon cycle technology,low carbon emission and energy consumption.It shows a slow increase in the overall development,but basically at the middle level.It needs adjustment and reform for increasing the transformation efforts.
出处
《中国软科学》
CSSCI
北大核心
2012年第1期107-115,共9页
China Soft Science
基金
黑龙江省哲学社会科学规划项目(10C020)
中国博士后科学基金资助项目(20090460871)
中央高校基本科研业务费专项资金资助(DL11CC14)
关键词
低碳循环
耦合发展测度
径向基神经网络
国有林区
low-carbon cycle
coupling development measure
RBF neural network
state-owned forest
