Abstract Machine learning methods have recently shown a broad application prospect in
biomass gasification modeling. However, a significant drawback of the machine learning …

In this paper, a hybrid temperature prediction model is developed for an industrial roller kiln
of lithium-ion battery cathode materials, which is based on first-principle model and moving …

In the development of soft sensors for industrial processes, the availability of data for data-
driven modeling is usually limited, which led to overfitting and lack of interpretability when …

A novel optimization framework for boiler combustion and selective catalytic reduction
systems (BCSCRSs) that accounts for flue gas temperature deviation and integrates prior …

准确的NO x 浓度预测对保障燃煤锅炉安全运行和降低污染物排放具有重要意义.
基于机器学习的NO x 排放浓度预测方法计算速度快, 拟合精度高, 但缺少可解释性 …

Ethylene glycol (EG) plays a pivotal role as a primary raw material in the polyester industry,
and the syngas-to-EG route has become a significant technical route in production. The …

Accurate modeling of open-circuit-voltage (OCV) plays important roles both in state-of-
charge (SOC) estimation and state-of-health (SOH) monitoring for lithium-ion batteries …

Different operating conditions of p-xylene oxidation have different influences on the product,
purified terephthalic acid. It is necessary to obtain the optimal combination of reaction …

In modeling, only information from the deviation between the output of the support vector
regression (SVR) model and the training sample is considered, whereas the other prior …