Aladejare AE, Onifade M, Lawal AI (2020) Application of metaheuristic based artificial neural network and multilinear regression for the prediction of higher heating values of fuels. Int J Coal Prep Util:1–22

Bach Q-V, Tran K-Q, Skreiberg Ø (2016) Hydrothermal pretreatment of fresh forest residues: effects of feedstock pre-drying. Biomass Bioenerg 85:76–83

Article
CAS
Google Scholar

Brewer CE, Chuang VJ, Masiello CA, Gonnermann H, Gao X, Dugan B, Driver LE, Panzacchi P, Zygourakis K, Davies CA (2014) New approaches to measuring biochar density and porosity. Biomass Bioenerg 66:176–185

Article
CAS
Google Scholar

Danso-Boateng E (2015) Biomass hydrothermal carbonisation for sustainable engineering. Doctoral dissertation, Loughborough University

Estiati I, Freire FB, Freire JT, Aguado R, Olazar M (2016) Fitting performance of artificial neural networks and empirical correlations to estimate higher heating values of biomass. Fuel 180:377–383

Article
CAS
Google Scholar

Ferreira C (2001) Gene expression programming: a new adaptive algorithm for solving problems. https://arxiv.org/abs/cs/0102027. Accessed 22 Jul 2020

Funke A, Ziegler F (2010) Hydrothermal carbonization of biomass: a summary and discussion of chemical mechanisms for process engineering. Biofuel BioprodBior 4(2):160–177

Article
CAS
Google Scholar

Gao L, Volpe M, Lucian M, Fiori L, Goldfarb JL (2019) Does hydrothermal carbonization as a biomass pretreatment reduce fuel segregation of coal-biomass blends during oxidation? Energy Convers. Manage 181:93–104

CAS
Google Scholar

Gevrey M, Dimopoulos I, Lek S (2003) Review and comparison of methods to study the contribution of variables in artificial neural network models. Ecol Model 160(3):249–264

Article
Google Scholar

Ghugare SB, Tiwary S, Tambe SS (2017) Computational intelligence based models for prediction of elemental composition of solid biomass fuels from proximate analysis. Int J Sys Ass EngMgt 8(4):2083–2096

Google Scholar

Guven A, Aytek A (2009) New approach for stage-discharge relationship: gene-expression programming. J HydrolEng 14(8):812–820

Google Scholar

Hansen JV, Meservy RD (1996) Learning experiments with genetic optimization of a generalized regression neural network. Decis Support Syst 18(3–4):317–325

Article
Google Scholar

He X, Liu Z, Niu W, Yang L, Zhou T, Qin D, Niu Z, Yuan Q (2018) Effects of pyrolysis temperature on the physicochemical properties of gas and biochar obtained from pyrolysis of crop residues. Energy 143:746–756

Article
CAS
Google Scholar

Holtmeyer ML, Li G, Kumfer BM, Li S, Axelbaum RL (2013) The impact of biomass cofiring on volatile flame length. Energ Fuel 27(12):7762–7771

Article
CAS
Google Scholar

Hwang I-H, Aoyama H, Matsuto T, Nakagishi T, Matsuo T (2012) Recovery of solid fuel from municipal solid waste by hydrothermal treatment using subcritical water. J Waste Manag 32(3):410–416

Article
CAS
Google Scholar

Jain AK, Mao J, Mohiuddin KM (1996) Artificial neural networks: a tutorial. Comput J 29(3):31–44

Google Scholar

Kambo HS, Dutta A (2014) Strength, storage, and combustion characteristics of densified lignocellulosic biomass produced via torrefaction and hydrothermal carbonization. Appl Energy 135:182–191

Article
CAS
Google Scholar

Kambo HS, Dutta A (2015) A comparative review of biochar and hydrochar in terms of production, physico-chemical properties, and applications. Renew SustEnerg Rev 45:359–378

Article
CAS
Google Scholar

Khandelwal M, Singh T (2010) Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks. Fuel 89(5):1101–1109

Article
CAS
Google Scholar

Kim D, Lee K, Park KY (2014) Hydrothermal carbonization of anaerobically digested sludge for solid fuel production and energy recovery. Fuel 130:120–125

Article
CAS
Google Scholar

Krylova AY, Zaitchenko V (2018) Hydrothermal carbonization of biomass: a review. Solid Fuel Chem 52(2):91–103

Article
CAS
Google Scholar

Kubacki ML, Ross AB, Jones JM, Williams A (2012) Small-scale co-utilisation of coal and biomass. Fuel 101:84–89

Article
CAS
Google Scholar

Lawal AI (2020) An artificial neural network-based mathematical model for the prediction of blast-induced ground vibration in granite quarries in Ibadan, Oyo State Nigeria. Sci Afr 8:e00413

Google Scholar

Lawal AI, Aladejare AE, Onifade M, Bada S, Idris MA (2020) Predictions of elemental composition of coal and biomass from their proximate analyses using ANFIS, ANN, and MLR. Int J Coal Sci Technol. https://doi.org/10.1007/s40789-020-00346-9

Article
Google Scholar

Lee J, Sohn D, Lee K, Park KY (2019) Solid fuel production through hydrothermal carbonization of sewage sludge and microalgae Chlorella sp. from wastewater treatment plant. Chemosphere 230:157–163

Article
CAS
PubMed
Google Scholar

Libra JA, Ro KS, Kammann C, Funke A, Berge ND, Neubauer Y, Titirici M-M, Fühner C, Bens O, Kern J (2011) Hydrothermal carbonization of biomass residuals: a comparative review of the chemistry, processes, and applications of wet and dry pyrolysis. Biofuels 2(1):71–106

Article
CAS
Google Scholar

Majumder AK, Jain R, Banerjee P, Barnwal J (2008) Development of a new proximate analysis based correlation to predict calorific value of coal. Fuel 87(13–14):3077–3081

Article
CAS
Google Scholar

Makwarela M, Bada S, Falcon R (2017) Co-firing combustion characteristics of different ages of Bambusabalcooa relative to a high ash coal. Renew Energy 105:656–664

Article
Google Scholar

Mierzwa-Hersztek M, Gondek K, Jewiarz M, Dziedzic K (2019) Assessment of energy parameters of biomass and biochars, leachability of heavy metals, and phytotoxicity of their ashes. J Mater Cycles Waste 21(4):786–800

Article
CAS
Google Scholar

Mumme J, Eckervogt L, Pielert J, Diakité M, Rupp F, Kern J (2011) Hydrothermal carbonization of anaerobically digested maize silage. BioresourTechnol 102(19):9255–9260

Article
CAS
Google Scholar

Onifade M, Lawal AI, Aladejare AE, Bada S, Idris MA (2019) Prediction of gross calorific value of solid fuels from their proximate analysis using soft computing and regression analysis. Int J Coal Prep Util:1–15

Park KY, Lee K, Kim D (2018) Characterized hydrochar of algal biomass for producing solid fuel through hydrothermal carbonization. BioresourTechnol 258:119–124

Article
CAS
Google Scholar

Parshetti GK, Hoekman SK, Balasubramanian R (2013) Chemical, structural and combustion characteristics of carbonaceous products obtained by hydrothermal carbonization of palm empty fruit bunches. BioresourTechnol 135:683–689

Article
CAS
Google Scholar

Patel N (2019) Hydrothermal Carbonization (HTC) of Marine Seaweed (Macroalgae) for Producing Hydro-Char. Masters thesis, Dalhousie University

Patel SU, Kumar BJ, Badhe YP, Sharma B, Saha S, Biswas S, Chaudhury A, Tambe SS, Kulkarni BD (2007) Estimation of gross calorific value of coals using artificial neural networks. Fuel 86(3):334–344

Article
CAS
Google Scholar

Peng C, Zhai Y, Zhu Y, Xu B, Wang T, Li C, Zeng G (2016) Production of char from sewage sludge employing hydrothermal carbonization: char properties, combustion behavior, and thermal characteristics. Fuel 176:110–118

Article
CAS
Google Scholar

Perlack RD, Eaton LM, Turhollow Jr AF, Langholtz MH, Brandt CC, Downing ME, Graham RL, Wright LL, Kavkewitz JM, Shamey AM (2011) US billion-ton update: biomass supply for a bioenergy and bioproducts industry. https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1015&context=abe_eng_reports. Accessed 16 Jul 2020

Pradhan P, Mahajani SM, Arora A (2018) Production and utilization of fuel pellets from biomass: a review. Fuel Process Technol 181:215–232

Article
CAS
Google Scholar

Reza MT, Uddin MH, Lynam JG, Hoekman SK, Coronella CJ (2014) Hydrothermal carbonization of loblolly pine: reaction chemistry and water balance. Biomass Convers Biorefin 4(4):311–321

Article
CAS
Google Scholar

Rousset P, Macedo L, Commandré J-M, Moreira A (2012) Biomass torrefaction under different oxygen concentrations and its effect on the composition of the solid by-product. J Anal Appl Pyrolysis 96:86–91

Article
CAS
Google Scholar

Saadat M, Khandelwal M, Monjezi M (2014) An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine. Iran J Rock MechGeotechEng 6(1):67–76

Google Scholar

Saba A, Saha P, Reza MT (2017) Co-Hydrothermal Carbonization of coal-biomass blend: Influence of temperature on solid fuel properties. Fuel Process Technol 167:711–720

Article
CAS
Google Scholar

Sadiku NA, Oluyege AO, Sadiku IB (2016) Analysis of the calorific and fuel value index of bamboo as a source of renewable biomass feedstock for energy generation in Nigeria. Lignocellulose 5(1):34–49

Google Scholar

Safarian S, Unnþórsson R, Richter C (2019) A review of biomass gasification modelling. Renew SustEnerg Rev 110:378–391

Article
CAS
Google Scholar

Said KO, Onifade M, Lawal AI, Githiria JM (2020a) An artificial intelligence-based model for the prediction of spontaneous combustion liability of coal based on its proximate analysis. Combust Sci Technol:1–18

Said KO, Onifade M, Lawal AI, Githiria JM (2020b) Computational intelligence-based models for predicting the spontaneous combustion liability of coal. Int J Coal Prep Util:1–25

Saidur R, Abdelaziz E, Demirbas A, Hossain M, Mekhilef S (2011) A review on biomass as a fuel for boilers. Renew SustEnerg Rev 15(5):2262–2289

Article
CAS
Google Scholar

Saldarriaga JF, Aguado R, Pablos A, Amutio M, Olazar M, Bilbao J (2015) Fast characterization of biomass fuels by thermogravimetric analysis (TGA). Fuel 140:744–751

Article
CAS
Google Scholar

Sevilla M, Fuertes AB (2009) The production of carbon materials by hydrothermal carbonization of cellulose. Carbon 47(9):2281–2289

Article
CAS
Google Scholar

Seyedsadr S, Al Afif R, Pfeifer C (2018) Hydrothermal carbonization of agricultural residues: a case study of the farm residues-based biogas plants. Carbon Resour Convers 1(1):81–85

Article
Google Scholar

Sheng C, Azevedo J (2005) Estimating the higher heating value of biomass fuels from basic analysis data. Biomass Bioenerg 28(5):499–507

Article
CAS
Google Scholar

Silakova M (2018) Hydrothermal carbonization of the tropical biomass.

Stemann J, Erlach B, Ziegler F (2013) Hydrothermal carbonisation of empty palm oil fruit bunches: laboratory trials, plant simulation, carbon avoidance, and economic feasibility. Waste Biomass Valori 4(3):441–454

Article
CAS
Google Scholar

Tekin K, Karagöz S, Bektaş S (2014) A review of hydrothermal biomass processing. Renew SustEnerg Rev 40:673–687

Article
CAS
Google Scholar

Teodorescu L, Sherwood D (2008) High energy physics event selection with gene expression programming. Comput Phys Commun 178(6):409–419

Article
CAS
Google Scholar

Uzun H, Yıldız Z, Goldfarb JL, Ceylan S (2017) Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis. BioresourTechnol 234:122–130

Article
CAS
Google Scholar

Vargas-Moreno J, Callejón-Ferre A, Pérez-Alonso J, Velázquez-Martí B (2012) A review of the mathematical models for predicting the heating value of biomass materials. Renew SustEnerg Rev 16(5):3065–3083

Article
CAS
Google Scholar

Volpe M, Goldfarb JL, Fiori L (2018) Hydrothermal carbonization of Opuntia ficus-indica cladodes: role of process parameters on hydrochar properties. BioresourTechnol 247:310–318

Article
CAS
Google Scholar

Wang T, Zhai Y, Zhu Y, Li C, Zeng G (2018) A review of the hydrothermal carbonization of biomass waste for hydrochar formation: Process conditions, fundamentals, and physicochemical properties. Renew SustEnerg Rev 90:223–247

Article
CAS
Google Scholar

Wasserman PD (1993) Advanced methods in neural computing. Wiley, New York

Google Scholar

Wiedner K, Naisse C, Rumpel C, Pozzi A, Wieczorek P, Glaser B (2013) Chemical modification of biomass residues during hydrothermal carbonization–What makes the difference, temperature or feedstock? Org Geochem 54:91–100

Article
CAS
Google Scholar

Xiong J-B, Pan Z-Q, Xiao X-F, Huang H-J, Lai F-Y, Wang J-X, Chen S-W (2019) Study on the hydrothermal carbonization of swine manure: The effect of process parameters on the yield/properties of hydrochar and process water. J Anal Appl Pyrolysis 144:104692

Article
CAS
Google Scholar

Xu Q, Qian Q, Quek A, Ai N, Zeng G, Wang J (2013) Hydrothermal carbonization of macroalgae and the effects of experimental parameters on the properties of hydrochars. ACS Sustain Chem Eng 1(9):1092–1101

Article
CAS
Google Scholar

Yang Y, Zhang Q (1997) A hierarchical analysis for rock engineering using artificial neural networks. Rock Mech Rock Eng 30(4):207–222

Article
Google Scholar

Zhang Z, Pang S (2019) Experimental investigation of tar formation and producer gas composition in biomass steam gasification in a 100 kW dual fluidised bed gasifier. Renew Energy 132:416–424

Article
CAS
Google Scholar

Zhu Y, Si Y, Wang X, Zhang W, Shao J, Yang H, Chen H (2018) Characterization of hydrochar pellets from hydrothermal carbonization of agricultural residues. Energ Fuel 32(11):11538–11546

Article
CAS
Google Scholar