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Application of MLP-ANN models for estimating the higher heating value of bamboo biomass

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ARTICLE DOWNLOAD

Application of MLP-ANN models for estimating the higher heating value of bamboo biomass

10$

Satyajit Pattanayak, Chanchal Loha, Lalhmingsanga Hauchhum & Lalsangzela Sailo 

Abstract

India is blessed with plenty of bamboo biomass resources. Particularly, in the north-east states of India, bamboo has the potential to supply the local energy need. In order to explore the feasibility of energy generation from these biomass materials, the first and the foremost thing is to know their higher heating values (HHVs). The artificial neural network (ANN) technique is used to predict the higher heating values of bamboo biomass. Three ANN models are developed based on input data from proximate analysis, ultimate analysis, and combined proximate-ultimate analysis. The prediction accuracies of these models are analyzed by comparing with the experimental data graphically and statistically. It is illustrated that ANN models could able to predict the HHV of biomass with reasonably high accuracy. Performance of the ANN models are also judge by comparing with the correlation-based models and found that all ANN models could able to predict the actual HHVs better than correlation-based models and the ANN model based on combined proximate-ultimate analysis gives the best accuracy with an average error of 2.49%.

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Year 2020
Language English
Format PDF
DOI 10.1007/s13399-020-00685-2