Artificial neural network regression model to predict flue gas temperature and emissions with the spectral norm of flame image

Golgiyaz, Sedat; Talu, Muhammed Fatih; Onat, Cem

doi:10.1016/j.fuel.2019.115827

Cited by 46 publications

(26 citation statements)

References 25 publications

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“…( There are several factors affecting NO x formation and each factor has a different effect on NO x formation. It is difficult to define the appropriate formula to estimate the NO x emissions [24,25]. Due to the non-linear characteristic of the relationship between operational parameters and NO x emissions, the ANN approach is a good tool for emissions.…”

Section: Results Of Annmentioning

confidence: 99%

“…Due to the non-linear characteristic of the relationship between operational parameters and NO x emissions, the ANN approach is a good tool for emissions. Golgiyaz et al [24] carried out an experimental study in 2019 to estimate flue gas temperature and emissions in a home-type hot coal-fired burner. Emission estimation was made with the ANN model prepared with the spectral form of flame image results obtained from a 22-minute experimental study.…”

Section: Results Of Annmentioning

confidence: 99%

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NOx emission modeling at cement plants with co-processing alternative fuels using ANN

Öztürk¹,

Öztürk

Karademır³

2021

Environmental Engineering Research

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The use of wastes as alternative fuel (AF) at the cement plants for clinkerization processes has increased in recent years as sustainable waste management. Such co-processing of AFs at cement plants causes some changes in the composition of the plant emissions, depending on waste type, kiln thermal power, thermal substitution rate, etc. Emissions of nitrogen oxides (NO x ) are among the major environmental concerns in these plants. The paper includes a modeling study of NO x emissions at a cement plant during the co-processing of AFs. Due to the nonlinear characteristic of the relationship between operational parameters and NO x emissions, the artificial neural network (ANN) approach was applied and studied. The study showed that NO x emissions can be predicted satisfactorily by using ANN at cement plants. Therefore, the model proposed may be used by cement plant operators to estimate their emission levels before starting the use of a new fuel source.

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Section: Results Of Annmentioning

confidence: 99%

Section: Results Of Annmentioning

confidence: 99%

NOx emission modeling at cement plants with co-processing alternative fuels using ANN

Öztürk¹,

Öztürk

Karademır³

2021

Environmental Engineering Research

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“…Its basic idea can be understood as the relationship between an unknown sample data and K samples as the nearest neighbor sample set. When k samples satisfy a specific category, the unknown samples are determined to belong to the category similarity expression, which is measured by Euler distance, and the expression is shown in Equation (1). 2 (1)…”

Section: Knn Algorithm Theorymentioning

confidence: 99%

“…Since the outbreak of novel coronavirus in late [1]. From the perspective of information technology innovation, the development of network security maintenance plan in combination with the needs of the times can play a fundamental role in the development of information technology [2].…”

Section: Introductionmentioning

confidence: 99%

Security design and application of Internet of things based on asymmetric encryption algorithm and neural network for COVID-19

Tang¹

2020

IFS

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During the period of COVID-19 protection, Internet of Things (IoT) has been widely used to fight the outbreak of pandemic. However, the security is a major issue of IoT. In this research, a new algorithm knn-bp is proposed by combining BP neural network and KNN. Knn-bp algorithm first predicts the collected sensor data. After the forecast is completed, the results are filtered. Compared with the data screened by traditional BP neural network, k-nearest-neighbor algorithm has good data stability in adjusting and supplementing outliers, and improves the accuracy of prediction model. This method has the advantages of high efficiency and small mean square error. The application of this method has certain reference value. Knn-bp algorithm greatly improves the accuracy and efficiency of the Internet of things. Internet of things network security is guaranteed. It plays an indelible role in the protection of COVID-19.

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“…[9] and [10] studies represent an overview of this topic. CCD cameras have been frequently used in flame imaging studies because these are widespread in the industry and these problems and superior aspects are well known [11,12,[21][22][23][24][25][26][27][28][13][14][15][16][17][18][19][20]. Various laser-based visualization techniques have been also used to investigate the combustion process [29,30].…”

Section: Introductionmentioning

confidence: 99%

Estimation of excess air coefficient on coal combustion processes via gauss model and artificial neural network

Golgiyaz

Talu

Daskin

et al. 2022

Alexandria Engineering Journal

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It is no doubt that the most important contributing cause of global efficiency of coal fired thermal systems is combustion efficiency. In this study, the relationship between the flame image obtained by a CCD camera and the excess air coefficient (k) has been modelled. The model has been obtained with a three-stage approach: 1) Data collection and synchronization: Obtaining the flame images by means of a CCD camera mounted on a 10 cm diameter observation port, k data has been coordinately measured and recorded by the flue gas analyzer. 2) Feature extraction: Gridding the flame image, it is divided into small pieces. The uniformity of each piece to the optimal flame image has been calculated by means of modelling with single and multivariable Gaussian, calculating of color probabilities and Gauss mixture approach. 3) Matching and testing: A multilayer artificial neural network (ANN) has been used for the matching of featureÀk.

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Artificial neural network regression model to predict flue gas temperature and emissions with the spectral norm of flame image

Cited by 46 publications

References 25 publications

NOx emission modeling at cement plants with co-processing alternative fuels using ANN

NOx emission modeling at cement plants with co-processing alternative fuels using ANN

Security design and application of Internet of things based on asymmetric encryption algorithm and neural network for COVID-19

Estimation of excess air coefficient on coal combustion processes via gauss model and artificial neural network

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