环境污染应急处置技术的CBR-MADM两步筛选法模型

摘要

突发环境污染事件进行应急处置时，需要在历史案例库和处置技术库的基础上通过筛选模型筛选出最适宜的应急处置技术.其中筛选的效率和准确性是构建技术筛选模型的首要因素，目前尚无较为满意的解决方案.本文结合案例推理技术(CBR)和模糊多属性群决策模型(MADM)的优势，建立了环境污染应急处置技术的CBR-MADM两步筛选法模型：第1步，先利用基于熵权G1法的CBR推理从案例库中匹配案例，再从相似度最高的几个案例中提取应急处置技术作为备选技术；第2步，利用 MADM 对备选技术进行筛选和决策.CBR-MADM两步筛选法既充分利用了历史处置经验，又极大地提高了应急处置技术的筛选速度和效率.将该方法应用于2012年底山西长治浊漳河苯胺泄漏污染事件中，成功筛选出“投加混凝剂-活性炭坝拦截”技术，同实际情况吻合，验证了其适用性和可行性.%As emergent environmental pollution accident occurs, it needed to screen the most appropriate emergency disposal technology through screening model based on the databases of historical cases and disposal technology. The efficiency and accuracy of screening was primary factor of establishing technical screening model, currently, there was no satisfactory solution. In this paper, a two-step screening model named CBR-MADM of environmental pollution emergency disposal technology was established which combined the advantages of Case-Based Reasoning (CBR) and Multiple Attribute Decision-Making (MADM). Firstly, matched cases was searched from case base based on CBR of entropy G1 method, then emergency disposal technology was extracted from several highest similarity cases. Secondly, MADM was used to screen and decide the optimal technology from those alternatives. CBR-MADM two-step screening method not only fully used historical disposal experience, but also greatly improved screening speed and efficiency of emergency disposal technology. CBR-MADM method was applied to aniline leakage pollution incident in Changzhi, Shanxi, 2012, coagulation-activated carbon adsorption interception technology was successfully screened, which perfectly matched actual solution.