基于灰色神经网络模型的生态足迹动态研究——以湖北省为例

Research on the dynamic tendency of ecological footprint based on the GNNM model——a case of Hubei Province

生态足迹（EF）作为一种定量测度可持续发展程度的方法,具有直观综合、操作简单、指标明确、可比性强等优点,但EF本身是一个静态指标,没有揭示生态系统的动态变化特征,灰色神经网络模型（GNNM）将灰色GM（1,1）模型与BP神经网络模型相组合能更好的拟合EF的动态发展.以湖北省（1991年～2011年）为对象,对GNNM模型进行了验证,结果表明：GNNM模型比单一灰色理论有着更高的精度和可靠度,预测精度提高了0.75％;21年间湖北省人均生态足迹增长了1.473 hm2/人,而人均生态承载力增加缓慢,总的生态赤字逐年加大,21年增加了1.389 hm2/人,未来湖北省生态足迹将继续加大,预计2020年将增加到3.659 hm2/人,是2011年的1.43倍,湖北省资源消耗已远超过资源承载力范围,处于不可持续状态,生产消费模式急待调整.

Ecological footprint,as a quantitative method to measure the degree of sustainable development,has the advantages of being intuitive,comprehension,simply operation,clear for index and strongly comparable.But EF is a static index hard to reveal the dynamic characteristics of ecological systems.The gray neural network model （GN-NM）,a combination of GM （1,1） and BP neural network model,can perfectly fit the dynamic changes of EF.Taking Hubei province （1991～2011） as a case,the effective-ness of GNNM is tested.The results show that：1） compared to the single GM （1,1）model,GNNM forecasting model is of a higher accuracy and reliability,increasing the accuracy forecasting by 0.75％; 2） during the 21 years,the per capita EF of Hubei province has increased 1.473 hm2 per person,while the per capita ecological carrying capacity rose slowly,so the ecological deficit has enlarged yearly and increased 1.389 hm2 per people; 3） the EF will increase to 3.659 hm2 per person in 2020,which is 1.43 times to 2011.The consumption of resources Hubei province has far exceeded its resource capacity and is in an unsustainable,so the production and consumption pattern should adjusted.