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

Pattanayak, Satyajit; Loha, Chanchal; Hauchhum, Lalhmingsanga; Sailo, Lalsangzela

doi:10.1007/s13399-020-00685-2

Cited by 35 publications

(18 citation statements)

References 20 publications

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“…Taking the C, H, and O averages values presented for 50 bamboo species (43.06% -46.58% for C, 5.16% -7.6% for H, and 46.02 % -50.35% for O), it can be stated that the values found in this work are either within or very close to those found in the literature [28].…”

Section: Discussionsupporting

confidence: 86%

Physical, Chemical and Mechanical Properties of Two-Age Bambusa tuldoides Briquettes

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Spadim

Eufrade-Junior

et al. 2020

The 1st International Electronic Conference on Forests—Forests for a Better Future: Sustainability, Innovation, Inter

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The use of natural resources as an energy source is a well-studied alternative to fossil fuels. Some studies present bamboo as promising biomass for energy generation, and its transformation into briquettes can be a way to take advantage of its production residues. This study's objective was to determine the physical and chemical properties of two bamboo ages (two and seven years old) of Bambusa vulgaris species to evaluate biomass quality and its briquettes for energy generation. Regarding the higher heating value, there was no difference between treatments means values, which were 17.8 MJ kg-1 and 18.2 MJ kg-1 for two and seven years old, respectively, and these values were slightly below those found in the literature for Bambusa spp. The mechanical durability was of low quality for both treatments at the testing conditions, so they are not recommended for briquette production. The proximate analysis results were quite near the literature and reinforce bamboo's positive qualities for biofuel usage.

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Section: Discussionsupporting

confidence: 86%

Physical, Chemical and Mechanical Properties of Two-Age Bambusa tuldoides Briquettes

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Spadim

Eufrade-Junior

et al. 2020

The 1st International Electronic Conference on Forests—Forests for a Better Future: Sustainability, Innovation, Inter

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“…This confirms the hierarchical pore feature of BC [28]. For the development of BC as biomass energy, the thermochemical process is one of the most effective and potential [29].…”

Section: Literature Review and Problem Statementsupporting

confidence: 75%

Development of bamboo charcoal and fragaria vesca powder photocatalysts in hydrogen production via water splitting

Sofi'i

Siswanto

Winarto

et al. 2020

EEJET

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“…The activation function is one of the most important requirements in training the FFNN and the most popular ones are the log-sigmoid, tan-sigmoid, and purelin. The best activation function after various trial and error was found to be tan-sigmoid which was also recommended by [51]. For HW model, the modelling was generally fine-tune in both M1 and M2 combinations to allow the architecture to run the simulation.…”

Section: Results Of Ai-based Modelsmentioning

confidence: 99%

Neurocomputing Modelling of Hydrochemical and Physical Properties of Groundwater Coupled with Spatial Clustering, GIS, and Statistical Techniques

Benaafi

Yassin

Usman³

et al. 2022

Sustainability

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Groundwater (GW) is a critical freshwater resource for billions of individuals worldwide. Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity. Reliable estimation of complex hydrochemical properties of GW is crucial for sustainable development. Real field and experimental studies in an agricultural area from the significant sandstone aquifers (Wajid Aquifer) were conducted. For the modelling purpose, three types of computational models, including the emerging Hammerstein–Wiener (HW), back propagation neural network (BPNN), and statistical multi-variate regression (MVR), were developed for the multi-station estimation of total dissolved solids (TDS) (mg/L) and total hardness (TH) (mg/L). A geographic information system (GIS) was used for the spatial variability assessment of 32 hydrochemical and physical properties of the GW aquifer. A comprehensive visualized literature review spanning several decades was conducted in order to gain an understanding of the existing research and debates relevant to a particular GW and artificial intelligence (AI) study. The experimental data, pre-processing, and feature selection were conducted to determine the most dominant variables for AI-based modelling. The estimation results were evaluated using determination coefficient (DC), mean bias error (MBE), mean square error (MSE), and root mean square error (RMSE). The outcomes proved that TDS (mg/L) and TH (mg/L) correlated more than 90% and 70–85% with Ca2+, Cl−, Br−, NO3−, and Fe, and Na+, SO42−, Mg2+, and F− combinations. HW-M1 justified promising among all the models with MBE = 1.41 × 10−11, 1.14 × 10−14, and MSE = 7.52 × 10−2, 3.88 × 10−11 for TDS (mg/L), TH (mg/L), respectively. The accuracy proved merit for the overall development of and practical estimation of hydrochemical variables (TDS, TH) (mg/L) and decision-making benchmarks.

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

Cited by 35 publications

References 20 publications

Physical, Chemical and Mechanical Properties of Two-Age Bambusa tuldoides Briquettes

Physical, Chemical and Mechanical Properties of Two-Age Bambusa tuldoides Briquettes

Development of bamboo charcoal and fragaria vesca powder photocatalysts in hydrogen production via water splitting

Neurocomputing Modelling of Hydrochemical and Physical Properties of Groundwater Coupled with Spatial Clustering, GIS, and Statistical Techniques

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