基于人工神经网络模型的森林资源安全评价——以大兴安岭阿木尔林业局为例

Evaluation on Forest Resources Security Based on BP Model—With Amur Forestry Bureau in Daxing'anling Mountains Forestry Region as a Case Study

参考国际森林可持续经营的相关进程,通过两轮的德尔菲法,调查中国林业经济管理理论与实践领域的12位专家,从森林资源的数量维度、质量维度、生态系统维度三个层面筛选并确定了反映森林资源安全的22个影响因子。通过实地调查,选取大兴安岭阿木尔林业局12年(1999—2010年)的相关数据,利用BP人工神经网络方法,对阿木尔林业局森林资源安全状态进行评价。结果表明:阿木尔林业局1999—2010年期间的森林资源安全状态的综合得分为0.876 5,表明这期间阿木尔林业局森林资源处于安全状态中。但是目前的这种安全状态是一种低效的安全状态,离高效的安全状态还有一段距离。提出了进一步增强森林资源安全程度,实现高效安全状态的对策。

Firstly,on the basis of consulting some international sustainable forest management processes and using a two-round Delphi survey of twelve theories and practice of forestry economic experts,22 factors of influence were chosen from forest quantity,quality and ecosystem. Secondly,by field investigation,data of Amur Forestry Bureau from 1999- 2010 were used and overall assessment was conducted using BP model. The result revealed that Amur Forestry Bureau forest resources security＇s score was 0. 876 5,it indicated its forest resources were secure. But they are at a low-effect level of security. At last the paper puts forward some countermeasures for strengthening forest security and realizing the efficient security of forest resources.