化工学报2024，Vol.75Issue(2)：593-603,11.DOI:10.11949/0438-1157.20231081
基于注意力模块化神经网络的城市固废焚烧过程氮氧化物排放预测
Prediction of NOx emissions for municipal solid waste incineration processes using attention modular neural network
摘要
Abstract
Real-time and accurate measurement of NOx emissions is indispensable to achieve closed-loop control of the denitrification process during municipal solid waste incineration(MSWI).To this end,this paper proposes a NOx emission prediction method for the MSWI process based on attention modular neural network(AMNN).First,it simulates the"divide and conquer"characteristics of the brain network in processing complex tasks,and uses the fuzzy C-means(FCM)clustering algorithm to divide the task to be predicted into multiple subtasks,thereby reducing the complexity of the prediction task.Second,to handle the sub-tasks efficiently,a self-organizing fuzzy neural network(SOFNN)is designed to construct the sub-models,in which a growing and pruning algorithm and an improved second-order learning algorithm work together to ensure both the learning efficiency and accuracy.Then,the attention mechanism is utilized to integrate the sub-models during the testing or application stages,which can further improve the generalization performance of this AMNN-based prediction model.Finally,the proposed prediction method is verified by Mackey-Glass time series and the real data from a MSWI plant in Beijing.关键词
城市固废焚烧/模块化神经网络/注意力机制/NOx排放预测Key words
municipal solid waste incineration/modular neural network/attention mechanism/NOx emissions prediction分类
信息技术与安全科学引用本文复制引用
蒙西,王岩,孙子健,乔俊飞..基于注意力模块化神经网络的城市固废焚烧过程氮氧化物排放预测[J].化工学报,2024,75(2):593-603,11.基金项目
国家重点研发计划项目(2019YFC1906004-2) （2019YFC1906004-2）
国家自然科学基金项目(622731013,61890930-5,62021003,62001012) （622731013,61890930-5,62021003,62001012）
