白腐真菌降解五氯苯酚过程的模拟  

Simulating the biodegradation process of pentachlorophenol (PCP) by white rot fungus by artificial neural network

作　　者：黄俊[1] 余刚[1] 张祖麟[1] 

机构地区：[1]清华大学环境科学与工程系,北京100084

出　　处：《计算机与应用化学》2005年第2期96-98,共3页Computers and Applied Chemistry

基　　金：国家重点基础研究专项经费资助(G1999045711);清华大学博士创新基金(092407058)

摘　　要：利用变步长BP算法,对白腐真菌生物降解五氯苯酚废水过程中污染物浓度变化的时间序列建立了人工神经网络预报模型,并利用该模型对生化降解过程的变化规律及趋势进行了研究。结果表明,模型的计算值与实测值之间的误差很小,对未来时刻数据的预测精度也较高,模型较好地反映了五氯苯酚含量在降解过程的变化规律。Artificial neural network (ANN) approach, using varied-pace back-propagation (BP) algorithm, was adopted to simulate the time series of pentachlorophenol (PCP) concentration during the biodegradation process by white rot fungi. The model was then used in the study on the changing rule of PCP concentration and the developing trend. The results showed high accuracy both for the present data and for the predicting data, which showed that the established ANN model had reflected the inherent rule of the biodegradation process of PCP wastewater. The study proved that ANN is a novel approach for the simulation of PCP biodegradation.

关 键 词：BP算法 五氯苯酚 白腐真菌 

分 类 号：X703[环境科学与工程—环境工程]