Dynamic Data Modeling of SCR Denitration System Based on Mutual Information
Wenjie Zhao, Luyao Zhang
Available Online February 2018.
- https://doi.org/10.2991/csece-18.2018.69How to use a DOI?
- coal-fired unit; SCR de-NOx system; mutual information; least squares support vector machine
- The establishment of accurate models is vital in parametric optimization of control systems, and the choice of input variables can directly affect the accuracy and complexity of the model. Therefore, this paper proposed a modeling method based on mutual information (MI) and least squares support vector machine (LSSVM). On the basis of MI, the problem of delay, the correlation and redundancy among variables were considered synthetically. The optimal ones were screened through field measured variables by MI, and chosen as the input of LSSVM for predictions of output NOx concentration. The results proved the method can decrease complexity, improve approximation and generalization capability.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Wenjie Zhao AU - Luyao Zhang PY - 2018/02 DA - 2018/02 TI - Dynamic Data Modeling of SCR Denitration System Based on Mutual Information PB - Atlantis Press SP - 321 EP - 324 SN - 2352-538X UR - https://doi.org/10.2991/csece-18.2018.69 DO - https://doi.org/10.2991/csece-18.2018.69 ID - Zhao2018/02 ER -