基于BP神经网络的低碳经济下区域农业协调发展研究

Coordinated development of regional agriculture in a framework of low carbon economy based on BP neural network

农业温室气体排放量逐渐增多,日益受到各国重视。低碳经济是倡导低能耗、低污染、低排放的经济模式,农业作为国民经济的基础产业,兼具碳源和碳汇功能,平衡农业生产碳源排放和碳汇量可以促进农业协调发展和可持续发展。基于低碳经济下区域农业协调发展的运行机理,运用BP神经网络方法构建低碳经济下区域农业协调发展评价模型,并采用我国区域农业面板数据为例进行实证研究。研究表明,低碳经济视角下区域农业经济发展水平与资源环境协调水平呈反向变化,我国经济发展较好的区域,资源环境协调度较差,而资源环境禀赋优良区域的经济发展较慢,社会协调度间差异较小。从创新农业技术减少碳源,合理布局农业生产增加碳汇,推动农业碳排放权交易增加农民收入等方面可提高低碳经济下区域农业协调发展的程度。

There is a growing worldwide concern on the increasing agricultural greenhouse gas emission. In response, low-carbon economy is promoted as the mode of low energy consumption, low pollution and low emission. As the foundation of national economy, agriculture both emits and absorbs carbon. To balance their volume is important for a coordinated and sustainable development in agriculture. This paper presents the mechanism of regional agricultural coordination in a framework of low-carbon economy. We develop an evaluation model based on BP neural network method and conduct empirical study with panel data in China. Studies show a negative relationship between the level of agricultural development and resource and environmental coordination. The better the regional economy develops, the poorer resource and environment coordination is. In comparison, the better resource and environmental coordination is, the slower regional economy develops. To improve regional agriculture coordination in the framework of a low-carbon economy, we need to apply innovative technology to reduce carbon emission, adopt a more rational distribution of agricultural production to increase carbon absorption, and promote agricultural carbon emission trading to increase peasants＇ income.