Comprehensive study on applications of artificial neural network in food process modeling

GVS Bhagya Raj, KK Dash - Critical reviews in food science and …, 2022 - Taylor & Francis
Artificial neural network (ANN) is a simplified model of the biological nervous system
consisting of nerve cells or neurons. The application of ANN to food process engineering is …

Artificial intelligence for control and optimization of boilers' performance and emissions: A review

MA Nemitallah, MA Nabhan, M Alowaifeer… - Journal of Cleaner …, 2023 - Elsevier
Burning fossil fuels is a major concern for global warming control. In Saudi Arabia, steam
power plants that relay on boilers to produce the steam accounted for around 50% of the …

Prediction of the NOx emissions from thermal power plant using long-short term memory neural network

G Yang, Y Wang, X Li - Energy, 2020 - Elsevier
Coal combustion in thermal power plant is the main source of the NO x emission. An
effective prediction model should be established for reducing NO x emission. This paper …

Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization …

T Zhang, Z Tang, J Wu, X Du, K Chen - Energy, 2021 - Elsevier
The prediction of crude oil prices has important research significance. The paper contributes
to the literature of hybrid models for forecasting crude oil prices. We apply ensemble …

A hybrid NOx emission prediction model based on CEEMDAN and AM-LSTM

X Wang, W Liu, Y Wang, G Yang - Fuel, 2022 - Elsevier
Frequent load changes pose a major challenge to the realization of pollutant control in
power plants. Accurate and reliable NOx concentration prediction models are of great …

Dynamic modeling of NOX emission in a 660 MW coal-fired boiler with long short-term memory

P Tan, B He, C Zhang, D Rao, S Li, Q Fang, G Chen - Energy, 2019 - Elsevier
With the rapid development of renewables, increasing demands for the participation of coal-
fired power plants in peak load regulation is expected. Frequent transients result in …

Dynamic modeling for NOx emission sequence prediction of SCR system outlet based on sequence to sequence long short-term memory network

P Xie, M Gao, H Zhang, Y Niu, X Wang - Energy, 2020 - Elsevier
As environmental protection policies become more stringent, lower and lower NOx emission
targets are required. Accurate NOx concentration prediction model plays an important role in …

Combustion optimization of ultra supercritical boiler based on artificial intelligence

Y Shi, W Zhong, X Chen, AB Yu, J Li - Energy, 2019 - Elsevier
A method for optimizing the combustion in an ultra-supercritical boiler is developed and
evaluated in a 660 MWe ultra-supercritical coal fired power plant. In this method, Artificial …

Modeling and reduction of NOX emissions for a 700 MW coal-fired boiler with the advanced machine learning method

P Tan, J Xia, C Zhang, Q Fang, G Chen - Energy, 2016 - Elsevier
This paper focuses on modeling and reducing NO X emissions for a coal-fired boilers with
advanced machine learning approaches. The novel ELM (extreme learning machine) model …

Developing an evolutionary deep learning framework with random forest feature selection and improved flow direction algorithm for NOx concentration prediction

H Ma, T Peng, C Zhang, C Ji, Y Li, MS Nazir - Engineering Applications of …, 2023 - Elsevier
The continuous change of load makes it difficult for the power plant to control the emission of
pollutants. A reliable NOx concentration prediction model is important to energy …