most citedAuto-Encoder-Extreme Learning Machine Model for Boiler NOx Emission Concentration Prediction

148 citations · 241 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2022★ 148 cited

Auto-Encoder-Extreme Learning Machine Model for Boiler NOx Emission Concentration Prediction

Zhenhao Tang, Shikui Wang, Xiangying Chai +3

An automatic encoder (AE) extreme learning machine (ELM)-AE-ELM model is proposed to predict the NOx emission concentration based on the combination of mutual information algorithm…

eess.SY2022★ 1 cited

Wind power ramp prediction algorithm based on wavelet deep belief network

Zhenhao Tang, Qingyu Meng, Shengxian Cao +3

The wind power ramp events threaten the power grid safety significantly. To improve the ramp prediction accuracy, a hybrid wavelet deep belief network algorithm with adaptive featu…

eess.SY2021

Data Driven based Dynamic Correction Prediction Model for NOx Emission of Coal Fired Boiler

Zhenhao Tang, Deyu Zhu, Yang Li

The real-time prediction of NOx emissions is of great significance for pollutant emission control and unit operation of coal-fired power plants. Aiming at dealing with the large ti…

eess.SP2021★ 92 cited

Non-intrusive load decomposition based on CNN-LSTM hybrid deep learning model

Xinxin Zhou, Jingru Feng, Yang Li

With the rapid development of science and technology, the problem of energy load monitoring and decomposition of electrical equipment has been receiving widespread attention from a…

eess.SP2021

Dynamic Prediction Model for NOx Emission of SCR System Based on Hybrid Data-driven Algorithms

Zhenhao Tang, Shikui Wang, Shengxian Cao +2

Aiming at the problem that delay time is difficult to determine and prediction accuracy is low in building prediction model of SCR system, a dynamic modeling scheme based on a hybr…