Prediction of Anoxic Sulfide Biooxidation Under Various HRTs Using Artificial Neural Networks

• 作 者: QAISAR MAHMOOD PING ZHENG DONG
• 机 构: DepartmentofEnvironmentalEngineering,InstituteofStatisticalGenetics,tUniversityofAridAgriculture,Uni
• 出 处: 生物医学与环境科学：英文版
• 发表日期: 2007年5期
• 关键词: 人工神经网络 硫化物预测 亚硝酸盐预测 成分分析 Artificial neural networks Effluent sulfide prediction

Objective During present investigation the data of a laboratory-scale anoxic sulfide oxidizing (ASO) reactor were used in a neural network system to predict its performance. Methods Five uncorrelated components of the influent wastewater were used as the