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Performance and exhaust emissions prediction of a CRDI assisted single cylinder diesel engine coupled with EGR using artificial neural network

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  1. Liang, Xingyu & Zhao, Bowen & Zhang, Fei & Liu, Qingling, 2019. "Compact research for maritime selective catalytic reduction reactor based on response surface methodology," Applied Energy, Elsevier, vol. 254(C).
  2. Sasanka Katreddi & Sujan Kasani & Arvind Thiruvengadam, 2022. "A Review of Applications of Artificial Intelligence in Heavy Duty Trucks," Energies, MDPI, vol. 15(20), pages 1-20, October.
  3. Raptotasios, Spiridon I. & Sakellaridis, Nikolaos F. & Papagiannakis, Roussos G. & Hountalas, Dimitrios T., 2015. "Application of a multi-zone combustion model to investigate the NOx reduction potential of two-stroke marine diesel engines using EGR," Applied Energy, Elsevier, vol. 157(C), pages 814-823.
  4. Eunhee Ko & Jungsoo Park, 2019. "Diesel Mean Value Engine Modeling Based on Thermodynamic Cycle Simulation Using Artificial Neural Network," Energies, MDPI, vol. 12(14), pages 1-17, July.
  5. Lu, Zhen & Liu, Mengyu & Shi, Lei & Wang, Tianyou & Lu, Tianlong & Wang, Huaiyin, 2022. "Numerical research of the injected exhaust gas recirculation strategy on a two-stroke low-speed marine diesel engine," Energy, Elsevier, vol. 244(PA).
  6. 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.
  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. Taghavifar, Hamid & Mardani, Aref & Karim Maslak, Haleh, 2015. "A comparative study between artificial neural networks and support vector regression for modeling of the dissipated energy through tire-obstacle collision dynamics," Energy, Elsevier, vol. 89(C), pages 358-364.
  10. 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.
  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. Taghavifar, Hadi & Khalilarya, Shahram & Jafarmadar, Samad, 2014. "Diesel engine spray characteristics prediction with hybridized artificial neural network optimized by genetic algorithm," Energy, Elsevier, vol. 71(C), pages 656-664.
  13. 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.
  14. Strušnik, Dušan & Marčič, Milan & Golob, Marjan & Hribernik, Aleš & Živić, Marija & Avsec, Jurij, 2016. "Energy efficiency analysis of steam ejector and electric vacuum pump for a turbine condenser air extraction system based on supervised machine learning modelling," Applied Energy, Elsevier, vol. 173(C), pages 386-405.
  15. 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).
  16. Kayadelen, Hasan Kayhan, 2018. "A multi-featured model for estimation of thermodynamic properties, adiabatic flame temperature and equilibrium combustion products of fuels, fuel blends, surrogates and fuel additives," Energy, Elsevier, vol. 143(C), pages 241-256.
  17. Evangelos G. Giakoumis & Alexandros T. Zachiotis, 2017. "Investigation of a Diesel-Engined Vehicle’s Performance and Emissions during the WLTC Driving Cycle—Comparison with the NEDC," Energies, MDPI, vol. 10(2), pages 1-19, February.
  18. Deb, Madhujit & Paul, Abhishek & Debroy, Durbadal & Sastry, G.R.K. & Panua, Raj Sekhar & Bose, P.K., 2015. "An experimental investigation of performance-emission trade off characteristics of a CI engine using hydrogen as dual fuel," Energy, Elsevier, vol. 85(C), pages 569-585.
  19. 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).
  20. 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.
  21. Evangelos G. Giakoumis & George Triantafillou, 2018. "Analysis of the Effect of Vehicle, Driving and Road Parameters on the Transient Performance and Emissions of a Turbocharged Truck," Energies, MDPI, vol. 11(2), pages 1-21, January.
  22. 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.
  23. Domínguez-Sáez, Aida & Rattá, Giuseppe A. & Barrios, Carmen C., 2018. "Prediction of exhaust emission in transient conditions of a diesel engine fueled with animal fat using Artificial Neural Network and Symbolic Regression," Energy, Elsevier, vol. 149(C), pages 675-683.
  24. 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.
  25. Roberto Finesso & Gilles Hardy & Claudio Maino & Omar Marello & Ezio Spessa, 2017. "A New Control-Oriented Semi-Empirical Approach to Predict Engine-Out NOx Emissions in a Euro VI 3.0 L Diesel Engine," Energies, MDPI, vol. 10(12), pages 1-26, November.
  26. 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.
  27. d’Ambrosio, Stefano & Finesso, Roberto & Fu, Lezhong & Mittica, Antonio & Spessa, Ezio, 2014. "A control-oriented real-time semi-empirical model for the prediction of NOx emissions in diesel engines," Applied Energy, Elsevier, vol. 130(C), pages 265-279.
  28. Silitonga, A.S. & Masjuki, H.H. & Ong, Hwai Chyuan & Sebayang, A.H. & Dharma, S. & Kusumo, F. & Siswantoro, J. & Milano, Jassinnee & Daud, Khairil & Mahlia, T.M.I. & Chen, Wei-Hsin & Sugiyanto, Bamban, 2018. "Evaluation of the engine performance and exhaust emissions of biodiesel-bioethanol-diesel blends using kernel-based extreme learning machine," Energy, Elsevier, vol. 159(C), pages 1075-1087.
  29. Zamboni, Giorgio & Moggia, Simone & Capobianco, Massimo, 2016. "Hybrid EGR and turbocharging systems control for low NOX and fuel consumption in an automotive diesel engine," Applied Energy, Elsevier, vol. 165(C), pages 839-848.
  30. Bhowmik, Mrinal & Muthukumar, P. & Anandalakshmi, R., 2019. "Experimental based multilayer perceptron approach for prediction of evacuated solar collector performance in humid subtropical regions," Renewable Energy, Elsevier, vol. 143(C), pages 1566-1580.
  31. Dey, Suman & Reang, Narath Moni & Majumder, Arindam & Deb, Madhujit & Das, Pankaj Kumar, 2020. "A hybrid ANN-Fuzzy approach for optimization of engine operating parameters of a CI engine fueled with diesel-palm biodiesel-ethanol blend," Energy, Elsevier, vol. 202(C).
  32. 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).
  33. Jarosław Ziółkowski & Mateusz Oszczypała & Jerzy Małachowski & Joanna Szkutnik-Rogoż, 2021. "Use of Artificial Neural Networks to Predict Fuel Consumption on the Basis of Technical Parameters of Vehicles," Energies, MDPI, vol. 14(9), pages 1-23, May.
  34. Aliakbari, Karim & Ebrahimi-Moghadam, Amir & Pahlavanzadeh, Mohammadsadegh & Moradi, Reza, 2023. "Performance characteristics and exhaust emissions of a single-cylinder diesel engine for different fuels: Experimental investigation and artificial intelligence network," Energy, Elsevier, vol. 284(C).
  35. Mehra, Roopesh Kumar & Duan, Hao & Luo, Sijie & Rao, Anas & Ma, Fanhua, 2018. "Experimental and artificial neural network (ANN) study of hydrogen enriched compressed natural gas (HCNG) engine under various ignition timings and excess air ratios," Applied Energy, Elsevier, vol. 228(C), pages 736-754.
  36. Stefano d’Ambrosio & Roberto Finesso & Gilles Hardy & Andrea Manelli & Alessandro Mancarella & Omar Marello & Antonio Mittica, 2021. "Model-Based Control of Torque and Nitrogen Oxide Emissions in a Euro VI 3.0 L Diesel Engine through Rapid Prototyping," Energies, MDPI, vol. 14(4), pages 1-25, February.
  37. Shahir, V.K. & Jawahar, C.P. & Suresh, P.R., 2015. "Comparative study of diesel and biodiesel on CI engine with emphasis to emissions—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 686-697.
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