| 基于人工神经网络的半连续式混合厌氧消化产气量预测 |
| |
| 引用本文： | 赖夏颉,张文阳,张良均,陈俊德.基于人工神经网络的半连续式混合厌氧消化产气量预测[J].环境工程学报,2015,9(1):459-463. |
| |
| 作者姓名： | 赖夏颉 张文阳 张良均 陈俊德 |
| |
| 作者单位： | 1.西南交通大学地球科学与环境工程学院, 成都 611756; 2.广州太普软件科技有限公司, 广州 510665 |
| |
| 摘 要： | 研究采用BP神经网络和模糊神经网络(FNN)模型对逐步提高有机负荷的半连续式餐厨垃圾和猪粪混合厌氧消化试验进行日产气量预测。结果表明,BP神经网络模型的预测准确率为77.63%,FNN模型为82.33%,2种模型均可用于产气预测,但FNN模型在传统神经网络模型基础上加入了模糊控制,可提高其准确率,更适用于混合厌氧消化产气量预测。
|
| 关 键 词： | 混合厌氧消化 半连续 BP神经网络 模糊神经网络 产气预测模型 |
| 收稿时间： | 2014-01-02 |
Prediction of gas production of semi-continuous anaerobic co-digestion based on artificial neural network |
| |
| Lai Xiajie,Zhang Wenyang,Zhang Liangjun,Chen Junde.Prediction of gas production of semi-continuous anaerobic co-digestion based on artificial neural network[J].Techniques and Equipment for Environmental Pollution Control,2015,9(1):459-463. |
| |
| Authors: | Lai Xiajie Zhang Wenyang Zhang Liangjun Chen Junde |
| |
| Institution: | 1.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China; 2.Guangzhou Tipdm Software Technology Co., Ltd, Guangzhou 510665, China |
| |
| Abstract: | The study established gas production prediction models based on BP neural network and fuzzy neural network (FNN) on a semi-continuous anaerobic co-digestion experiment of kitchen waste and pig manure with gradually increasing organic loading rate.The results showed that the prediction accuracy of BP neural network model was 77.63%, and that of the FNN model was 82.33%.Both models can be used to predict gas production, but the FNN model, which joined fuzzy control in the traditional neural network to improve its accuracy, is more suitable for the gas prediction of anaerobic co-digestion. |
| |
| Keywords: | anaerobic co-digestion semi-continuous BP neural network fuzzy neural network gas production prediction model |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《环境工程学报》浏览原始摘要信息 |
| 点击此处可从《环境工程学报》下载免费的PDF全文 |
|
