2020
DOI: 10.1016/j.energy.2020.118457
|View full text |Cite
|
Sign up to set email alerts
|

A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus®

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
16
0
1

Year Published

2022
2022
2024
2024

Publication Types

Select...
10

Relationship

1
9

Authors

Journals

citations
Cited by 59 publications
(17 citation statements)
references
References 68 publications
0
16
0
1
Order By: Relevance
“…In chemical engineering, supervised learning methods (mainly regressionbased methods) are the widely used, in areas such as absorption [13], sludge treatment [14], reactor modelling [15], etc. ML regression methods reported in literature involves the use of linear regression [12], decision tree [16], Support Vector Regressions (SVR) [17], Artificial Neural Network (ANN) [18] etc. The wide application of these techniques in catalysis has recently been reported by Takahashi et al [19].…”
Section: Machine Learning Methods Are Typically Approached Asmentioning
confidence: 99%
“…In chemical engineering, supervised learning methods (mainly regressionbased methods) are the widely used, in areas such as absorption [13], sludge treatment [14], reactor modelling [15], etc. ML regression methods reported in literature involves the use of linear regression [12], decision tree [16], Support Vector Regressions (SVR) [17], Artificial Neural Network (ANN) [18] etc. The wide application of these techniques in catalysis has recently been reported by Takahashi et al [19].…”
Section: Machine Learning Methods Are Typically Approached Asmentioning
confidence: 99%
“…Unlike the model that works based on the chemical equilibrium in the real case, conversion rates of the reaction depend on the kinetics and residence time. This situation was discussed by some researchers who studied it with the equilibrium model [26,[37][38][39]. Hereby, the validation of the downdraft gasifier model was completed successfully, and the newly developed model was found to be reasonably acceptable.…”
Section: Model Validationmentioning
confidence: 99%
“…Both models shown in Figure 3 contain an input layer, a hidden layer or layers, and an output layer. When ANNs contain more than one hidden layer they are referred to as deep neural networks (DNNs) [73]. Beyond this basic description of neural networks in Figure 3, details about various neural network architectures can be found in previous studies [74].…”
Section: Ann Models With Gasificationmentioning
confidence: 99%