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Artificial neural networks modelling of engine-out responses for a light-duty diesel engine fuelled with biodiesel blends

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  1. Iftikhar Ahmad & Adil Sana & Manabu Kano & Izzat Iqbal Cheema & Brenno C. Menezes & Junaid Shahzad & Zahid Ullah & Muzammil Khan & Asad Habib, 2021. "Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions," Energies, MDPI, vol. 14(16), pages 1-27, August.
  2. Bendu, Harisankar & Deepak, B.B.V.L. & Murugan, S., 2017. "Multi-objective optimization of ethanol fuelled HCCI engine performance using hybrid GRNN–PSO," Applied Energy, Elsevier, vol. 187(C), pages 601-611.
  3. Bahri, Bahram & Aziz, Azhar Abdul & Shahbakhti, Mahdi & Muhamad Said, Mohd Farid, 2013. "Understanding and detecting misfire in an HCCI engine fuelled with ethanol," Applied Energy, Elsevier, vol. 108(C), pages 24-33.
  4. Yusri, I.M. & Abdul Majeed, A.P.P. & Mamat, R. & Ghazali, M.F. & Awad, Omar I. & Azmi, W.H., 2018. "A review on the application of response surface method and artificial neural network in engine performance and exhaust emissions characteristics in alternative fuel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 665-686.
  5. Talebian-Kiakalaieh, Amin & Amin, Nor Aishah Saidina & Zarei, Alireza & Noshadi, Iman, 2013. "Transesterification of waste cooking oil by heteropoly acid (HPA) catalyst: Optimization and kinetic model," Applied Energy, Elsevier, vol. 102(C), pages 283-292.
  6. Rezaei, Javad & Shahbakhti, Mahdi & Bahri, Bahram & Aziz, Azhar Abdul, 2015. "Performance prediction of HCCI engines with oxygenated fuels using artificial neural networks," Applied Energy, Elsevier, vol. 138(C), pages 460-473.
  7. Lotfan, S. & Ghiasi, R. Akbarpour & Fallah, M. & Sadeghi, M.H., 2016. "ANN-based modeling and reducing dual-fuel engine’s challenging emissions by multi-objective evolutionary algorithm NSGA-II," Applied Energy, Elsevier, vol. 175(C), pages 91-99.
  8. Song Hu & Stefano d’Ambrosio & Roberto Finesso & Andrea Manelli & Mario Rocco Marzano & Antonio Mittica & Loris Ventura & Hechun Wang & Yinyan Wang, 2019. "Comparison of Physics-Based, Semi-Empirical and Neural Network-Based Models for Model-Based Combustion Control in a 3.0 L Diesel Engine," Energies, MDPI, vol. 12(18), pages 1-41, September.
  9. Javed, Syed & Baig, Rahmath Ulla & Murthy, Y.V.V. Satyanarayana, 2018. "Study on noise in a hydrogen dual-fuelled zinc-oxide nanoparticle blended biodiesel engine and the development of an artificial neural network model," Energy, Elsevier, vol. 160(C), pages 774-782.
  10. Roy, Sumit & Banerjee, Rahul & Bose, Probir Kumar, 2014. "Performance and exhaust emissions prediction of a CRDI assisted single cylinder diesel engine coupled with EGR using artificial neural network," Applied Energy, Elsevier, vol. 119(C), pages 330-340.
  11. Tarafdar, Anirban & Majumder, P. & Deb, Madhujit & Bera, U.K., 2023. "Application of a q-rung orthopair hesitant fuzzy aggregated Type-3 fuzzy logic in the characterization of performance-emission profile of a single cylinder CI-engine operating with hydrogen in dual fu," Energy, Elsevier, vol. 269(C).
  12. Roy, Sumit & Ghosh, Ashmita & Das, Ajoy Kumar & Banerjee, Rahul, 2015. "Development and validation of a GEP model to predict the performance and exhaust emission parameters of a CRDI assisted single cylinder diesel engine coupled with EGR," Applied Energy, Elsevier, vol. 140(C), pages 52-64.
  13. Hosseini, Seyyed Hassan & Taghizadeh-Alisaraei, Ahmad & Ghobadian, Barat & Abbaszadeh-Mayvan, Ahmad, 2020. "Artificial neural network modeling of performance, emission, and vibration of a CI engine using alumina nano-catalyst added to diesel-biodiesel blends," Renewable Energy, Elsevier, vol. 149(C), pages 951-961.
  14. Simsek, Suleyman & Uslu, Samet & Simsek, Hatice, 2022. "Proportional impact prediction model of animal waste fat-derived biodiesel by ANN and RSM technique for diesel engine," Energy, Elsevier, vol. 239(PD).
  15. Çay, Yusuf & Korkmaz, Ibrahim & Çiçek, Adem & Kara, Fuat, 2013. "Prediction of engine performance and exhaust emissions for gasoline and methanol using artificial neural network," Energy, Elsevier, vol. 50(C), pages 177-186.
  16. Mohamed Ismail, Harun & Ng, Hoon Kiat & Gan, Suyin & Lucchini, Tommaso, 2013. "Computational study of biodiesel–diesel fuel blends on emission characteristics for a light-duty diesel engine using OpenFOAM," Applied Energy, Elsevier, vol. 111(C), pages 827-841.
  17. WenBo Xiao & Gina Nazario & HuaMing Wu & HuaMing Zhang & Feng Cheng, 2017. "A neural network based computational model to predict the output power of different types of photovoltaic cells," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-8, September.
  18. Rajkumar, Sundararajan & Das, Arnab & Thangaraja, Jeyaseelan, 2022. "Integration of artificial neural network, multi-objective genetic algorithm and phenomenological combustion modelling for effective operation of biodiesel blends in an automotive engine," Energy, Elsevier, vol. 239(PA).
  19. Lešnik, Luka & Vajda, Blaž & Žunič, Zoran & Škerget, Leopold & Kegl, Breda, 2013. "The influence of biodiesel fuel on injection characteristics, diesel engine performance, and emission formation," Applied Energy, Elsevier, vol. 111(C), pages 558-570.
  20. Wong, Pak Kin & Wong, Ka In & Vong, Chi Man & Cheung, Chun Shun, 2015. "Modeling and optimization of biodiesel engine performance using kernel-based extreme learning machine and cuckoo search," Renewable Energy, Elsevier, vol. 74(C), pages 640-647.
  21. Sun, Ping & Zhang, Jufang & Dong, Wei & Li, Decheng & Yu, Xiumin, 2023. "Prediction of oxygen-enriched combustion and emission performance on a spark ignition engine using artificial neural networks," Applied Energy, Elsevier, vol. 348(C).
  22. Ganesan, P. & Rajakarunakaran, S. & Thirugnanasambandam, M. & Devaraj, D., 2015. "Artificial neural network model to predict the diesel electric generator performance and exhaust emissions," Energy, Elsevier, vol. 83(C), pages 115-124.
  23. Bishop, Justin D.K. & Stettler, Marc E.J. & Molden, N. & Boies, Adam M., 2016. "Engine maps of fuel use and emissions from transient driving cycles," Applied Energy, Elsevier, vol. 183(C), pages 202-217.
  24. Wong, Ka In & Wong, Pak Kin & Cheung, Chun Shun & Vong, Chi Man, 2013. "Modeling and optimization of biodiesel engine performance using advanced machine learning methods," Energy, Elsevier, vol. 55(C), pages 519-528.
  25. Subrata Bhowmik & Rajsekhar Panua & Subrata K Ghosh & Abhishek Paul & Durbadal Debroy, 2018. "Prediction of performance and exhaust emissions of diesel engine fuelled with adulterated diesel: An artificial neural network assisted fuzzy-based topology optimization," Energy & Environment, , vol. 29(8), pages 1413-1437, December.
  26. Siami-Irdemoosa, Elnaz & Dindarloo, Saeid R., 2015. "Prediction of fuel consumption of mining dump trucks: A neural networks approach," Applied Energy, Elsevier, vol. 151(C), pages 77-84.
  27. Chang, Yu-Cheng & Lee, Wen-Jhy & Lin, Sheng-Lun & Wang, Lin-Chi, 2013. "Green energy: Water-containing acetone–butanol–ethanol diesel blends fueled in diesel engines," Applied Energy, Elsevier, vol. 109(C), pages 182-191.
  28. Manieniyan, V. & Vinodhini, G. & Senthilkumar, R. & Sivaprakasam, S., 2016. "Wear element analysis using neural networks of a DI diesel engine using biodiesel with exhaust gas recirculation," Energy, Elsevier, vol. 114(C), pages 603-612.
  29. Mariani, F. & Grimaldi, C.N. & Battistoni, M., 2014. "Diesel engine NOx emissions control: An advanced method for the O2 evaluation in the intake flow," Applied Energy, Elsevier, vol. 113(C), pages 576-588.
  30. Kshirsagar, Charudatta M. & Anand, Ramanathan, 2017. "Artificial neural network applied forecast on a parametric study of Calophyllum inophyllum methyl ester-diesel engine out responses," Applied Energy, Elsevier, vol. 189(C), pages 555-567.
  31. Bhowmik, Subrata & Paul, Abhishek & Panua, Rajsekhar & Ghosh, Subrata Kumar & Debroy, Durbadal, 2018. "Performance-exhaust emission prediction of diesosenol fueled diesel engine: An ANN coupled MORSM based optimization," Energy, Elsevier, vol. 153(C), pages 212-222.
  32. Bahri, Bahram & Shahbakhti, Mahdi & Kannan, Kaushik & Aziz, Azhar Abdul, 2016. "Identification of ringing operation for low temperature combustion engines," Applied Energy, Elsevier, vol. 171(C), pages 142-152.
  33. Chang, Yu-Cheng & Lee, Wen-Jhy & Wang, Lin-Chi & Yang, Hsi-Hsien & Cheng, Man-Ting & Lu, Jau-Huai & Tsai, Ying I. & Young, Li-Hao, 2014. "Effects of waste cooking oil-based biodiesel on the toxic organic pollutant emissions from a diesel engine," Applied Energy, Elsevier, vol. 113(C), pages 631-638.
  34. Lin, Jiefeng & Gaustad, Gabrielle & Trabold, Thomas A., 2013. "Profit and policy implications of producing biodiesel–ethanol–diesel fuel blends to specification," Applied Energy, Elsevier, vol. 104(C), pages 936-944.
  35. Babu, D. & Thangarasu, Vinoth & Ramanathan, Anand, 2020. "Artificial neural network approach on forecasting diesel engine characteristics fuelled with waste frying oil biodiesel," Applied Energy, Elsevier, vol. 263(C).
  36. Channapattana, S.V. & Pawar, Abhay A. & Kamble, Prashant G., 2017. "Optimisation of operating parameters of DI-CI engine fueled with second generation Bio-fuel and development of ANN based prediction model," Applied Energy, Elsevier, vol. 187(C), pages 84-95.
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