BP神经网络预测油田废水混凝处理效果
Study on Oil Field Sewage Treated by Coagulation
采用均匀设计方法选择神经网络的训练样本，并建立了基于BP人工神经网络的油田废水混凝处理系统的数学模型。利用该模型对实验数据进行预测，结果表明模型的预测值与实测值的平均绝对误差仅为0.74%。可见这种方法预测精度高，具有一定的实际应用价值
Uniform design method was used to choose training samples of neural network, and a mathematic model of oil field sewage treated by coagulation process based on BP artificial neural network was established. The model was then to predict some experimental data, the results indicate that the average absolute error between computed data and experimental data was only 0.74%. It is obvious that the method has high predicting accuracy and is worth of application.
林衍、王仁雷
废物处理、废物综合利用自动化技术、自动化技术设备计算技术、计算机技术
均匀设计 BP神经网络 混凝 油田废水
Uniform designBP neural networkCoagulationOil field sewage
林衍,王仁雷.BP神经网络预测油田废水混凝处理效果[EB/OL].(2004-12-13)[2025-08-24].http://www.paper.edu.cn/releasepaper/content/200412-27.点此复制
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