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Multivariate Time Series Prediction for Co2 Concentration and Flue Gas Flowrate from Biomass-Fired Power Plant

https://doi.org/10.2139/ssrn.4462625
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Role of input features in developing data-driven models for building thermal demand forecast
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Performance of a portable NIR spectrometer for the determination of moisture content of industrial wood chips fuel
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Rapid determination of diesel fuel properties by near-infrared spectroscopy
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Prediction of SOx–NOx emission from a coal-fired CFB power plant with machine learning: Plant data learned by deep neural network and least square support vector machine
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A comparison between single layer and multilayer artificial neural networks in predicting diesel fuel properties using near infrared spectrum
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Identification of Repeatedly Frozen Meat Based on Near-Infrared Spectroscopy Combined with Self-Organizing Competitive Neural Networks
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Artificial neural networks: a tutorial
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A Deep Learning Model for Measuring Oxygen Content of Boiler Flue Gas
inferredcites →https://doi.org/10.1109/ccdc.2017.7978732openalex-extracted
Artificial neural networks model for predicting oxygen content in flue gas of power plant
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ANN-based Soft Sensing of Oxygen Content in Boiler Air-flue Gas System
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Content measurement of textile mixture by near infrared spectroscopy based on BP neural network
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Performance analysis of short-term electricity demand with meteorological parameters
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SO2 Prediction for Wet Flue Gas Desulfurization Based on Improved Long and Short-Term Memory
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Long Short-Term Memory
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LSTM-based soft sensor design for oxygen content of flue gas in coal-fired power plant
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Developing an ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases
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Prediction and Control of the Nitrogen Oxides Emission for Environmental Protection Goal Based on Data-Driven Model in the SCR de-NOx System
inferredcites →https://doi.org/10.48550/arxiv.2001.08317openalex-extracted
Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case
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