메뉴 건너뛰기




Volumn 37, Issue , 2012, Pages 217-225

Prediction of engine performance for an alternative fuel using artificial neural network

Author keywords

Artificial neural network; Methanol engine performance; Spark ignition engine

Indexed keywords

ANN PREDICTION; ARTIFICIAL NEURAL NETWORK; BRAKE SPECIFIC FUEL CONSUMPTION; EFFECTIVE PRESSURE; ENGINE PERFORMANCE; ENGINE SPEED; ENGINE TORQUE; EXHAUST GAS TEMPERATURES; EXPERIMENTAL DATA; FUEL FLOW; INPUT LAYERS; INTAKE MANIFOLD; MEAN ERRORS; MEAN TEMPERATURE; METHANOL ENGINE; METHANOL ENGINE PERFORMANCE; MODEL-BASED OPC; OUTPUT LAYER; STANDARD BACK PROPAGATION ALGORITHMS; TESTING DATA; TRAINING AND TESTING; WATER ENTRANCE;

EID: 84856393468     PISSN: 13594311     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.applthermaleng.2011.11.019     Document Type: Article
Times cited : (174)

References (33)
  • 2
    • 84856393913 scopus 로고    scopus 로고
    • The effect of gasoline-methanol blends on the engine performance and exhaust emission in a spark ignition engine
    • May 13-15; Karabük, Turkey
    • A. Calisir, M. Gumus, The effect of gasoline-methanol blends on the engine performance and exhaust emission in a spark ignition engine. IATS 2009: Proceedings of the 5th International Advanced Technologies Symposium; 2009 May 13-15; Karabük, Turkey. p. 189-1898.
    • (2009) IATS 2009: Proceedings of the 5th International Advanced Technologies Symposium , pp. 189-1898
    • Calisir, A.1    Gumus, M.2
  • 3
    • 79951956519 scopus 로고    scopus 로고
    • The use of pure methanol as fuel at high compression ratio in a single cylinder gasoline engine
    • M.B. Celik, B. Ozdalyan, and F. Alkan The use of pure methanol as fuel at high compression ratio in a single cylinder gasoline engine Fuel 90 2011 1591 1598
    • (2011) Fuel , vol.90 , pp. 1591-1598
    • Celik, M.B.1    Ozdalyan, B.2    Alkan, F.3
  • 4
    • 77956614163 scopus 로고    scopus 로고
    • Effect of injection and ignition timings on performance and emissions from a spark-ignition engine fueled with methanol
    • J. Li, C.M. Gong, Y. Su, H.L. Dou, and X.J. Liu Effect of injection and ignition timings on performance and emissions from a spark-ignition engine fueled with methanol Fuel 89 2010 3919 3925
    • (2010) Fuel , vol.89 , pp. 3919-3925
    • Li, J.1    Gong, C.M.2    Su, Y.3    Dou, H.L.4    Liu, X.J.5
  • 5
    • 77955270102 scopus 로고    scopus 로고
    • Engine performance and exhaust gas emissions of methanol and ethanol-diesel blends
    • C. Sayin Engine performance and exhaust gas emissions of methanol and ethanol-diesel blends Fuel 89 2010 3410 3415
    • (2010) Fuel , vol.89 , pp. 3410-3415
    • Sayin, C.1
  • 8
    • 12244264442 scopus 로고    scopus 로고
    • Estimation of the radon concentration in soil related to the environmental parameters by a modified adaline neural network
    • A. Negarestani, S. Setayeshi, M. Ghannadi-Maragheh, and B. Akashe Estimation of the radon concentration in soil related to the environmental parameters by a modified adaline neural network Applied Radiation and Isotopes 58 2 2003 269 273
    • (2003) Applied Radiation and Isotopes , vol.58 , Issue.2 , pp. 269-273
    • Negarestani, A.1    Setayeshi, S.2    Ghannadi-Maragheh, M.3    Akashe, B.4
  • 9
    • 45449100528 scopus 로고    scopus 로고
    • Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers
    • M. Taheri, and A. Mohebbi Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers Journal of Hazardous Materials 157 2008 122 129
    • (2008) Journal of Hazardous Materials , vol.157 , pp. 122-129
    • Taheri, M.1    Mohebbi, A.2
  • 10
    • 79955637700 scopus 로고    scopus 로고
    • Application of regression and artificial neural network analysis in modeling of tool-chip interface temperature in machining
    • 10.1016/j.eswa.2011.03.044
    • I. Korkut, A. Acir, and M. Boy Application of regression and artificial neural network analysis in modeling of tool-chip interface temperature in machining Expert Systems with Applications 2011 10.1016/j.eswa.2011.03.044
    • (2011) Expert Systems with Applications
    • Korkut, I.1    Acir, A.2    Boy, M.3
  • 11
    • 64049095408 scopus 로고    scopus 로고
    • Modelling of the cutting tool stresses in machining of Inconel 718 using artificial neural networks
    • A. Kurt Modelling of the cutting tool stresses in machining of Inconel 718 using artificial neural networks Expert Systems with Applications 36 2009 9645 9657
    • (2009) Expert Systems with Applications , vol.36 , pp. 9645-9657
    • Kurt, A.1
  • 12
    • 80052947315 scopus 로고    scopus 로고
    • Diesel engine condition monitoring using a multi-net neural network system with nonintrusive sensors
    • J. Porteiro, J. Collazo, D. Patiño, and J.L. Míguez Diesel engine condition monitoring using a multi-net neural network system with nonintrusive sensors Applied Thermal Engineering 31 2011 4097 4105
    • (2011) Applied Thermal Engineering , vol.31 , pp. 4097-4105
    • Porteiro, J.1    Collazo, J.2    Patiño, D.3    Míguez, J.L.4
  • 13
    • 78049443019 scopus 로고    scopus 로고
    • Predictive analysis of combined burner parameter effects on oxy-fuel flames
    • T. Boushaki, S. Guessasma, and J.C. Sautet Predictive analysis of combined burner parameter effects on oxy-fuel flames Applied Thermal Engineering 31 2011 202 212
    • (2011) Applied Thermal Engineering , vol.31 , pp. 202-212
    • Boushaki, T.1    Guessasma, S.2    Sautet, J.C.3
  • 14
    • 77349119394 scopus 로고    scopus 로고
    • Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks
    • M. Khandelwal, and T.N. Singh Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks Fuel 89 2010 1101 1109
    • (2010) Fuel , vol.89 , pp. 1101-1109
    • Khandelwal, M.1    Singh, T.N.2
  • 15
    • 59349083164 scopus 로고    scopus 로고
    • Prediction of optimized pretreatment process parameters for biodiesel production using ANN and GA
    • M. Rajendra, P.C. Jena, and H. Raheman Prediction of optimized pretreatment process parameters for biodiesel production using ANN and GA Fuel 88 2009 868 875
    • (2009) Fuel , vol.88 , pp. 868-875
    • Rajendra, M.1    Jena, P.C.2    Raheman, H.3
  • 16
    • 79952535556 scopus 로고    scopus 로고
    • Neural network (ANN) approach to biodiesel analysis: Analysis of biodiesel density, kinematic viscosity, methanol and water contents using near infrared (NIR) spectroscopy
    • R.M. Balabin, E.I. Lomakina, and R.Z. Safieva Neural network (ANN) approach to biodiesel analysis: analysis of biodiesel density, kinematic viscosity, methanol and water contents using near infrared (NIR) spectroscopy Fuel 90 2011 2007 2015
    • (2011) Fuel , vol.90 , pp. 2007-2015
    • Balabin, R.M.1    Lomakina, E.I.2    Safieva, R.Z.3
  • 17
    • 56049096202 scopus 로고    scopus 로고
    • Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network
    • B. Ghobadian, H. Rahimi, A.M. Nikbakht, G. Najafi, and T.F. Yusaf Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network Renewable Energy 34 2009 976 982
    • (2009) Renewable Energy , vol.34 , pp. 976-982
    • Ghobadian, B.1    Rahimi, H.2    Nikbakht, A.M.3    Najafi, G.4    Yusaf, T.F.5
  • 18
    • 70749096750 scopus 로고    scopus 로고
    • Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends
    • M. Kiani Deh Kiani, B. Ghobadian, T. Tavakoli, A.M. Nikbakht, and G. Najafi Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends Energy 35 2010 65 69
    • (2010) Energy , vol.35 , pp. 65-69
    • Kiani Deh Kiani, M.1    Ghobadian, B.2    Tavakoli, T.3    Nikbakht, A.M.4    Najafi, G.5
  • 20
    • 20444464409 scopus 로고    scopus 로고
    • Modelling the correlation between cutting and process parameters in highspeed machining of Inconel 718 alloy using an artificial neural network
    • E.O. Ezugwu, D.A. Fadare, J. Bonneya, R.B.D. Silva, and W.F. Sales Modelling the correlation between cutting and process parameters in highspeed machining of Inconel 718 alloy using an artificial neural network International Journal of Machine Tools and Manufacture 45 2005 1375 1385
    • (2005) International Journal of Machine Tools and Manufacture , vol.45 , pp. 1375-1385
    • Ezugwu, E.O.1    Fadare, D.A.2    Bonneya, J.3    Silva, R.B.D.4    Sales, W.F.5
  • 21
    • 33746906672 scopus 로고    scopus 로고
    • A study of surface roughness in drilling using mathematical analysis and neural networks
    • C. Sanjay, and C. Jyothi A study of surface roughness in drilling using mathematical analysis and neural networks International Journal of Advanced Manufacturing Technology 29 2006 846 852
    • (2006) International Journal of Advanced Manufacturing Technology , vol.29 , pp. 846-852
    • Sanjay, C.1    Jyothi, C.2
  • 22
    • 44749086674 scopus 로고    scopus 로고
    • Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models
    • J.P. Davim, V.N. Gaitonde, and S.R. Karmik Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models Journal of Material Processing 205 2008 16 23
    • (2008) Journal of Material Processing , vol.205 , pp. 16-23
    • Davim, J.P.1    Gaitonde, V.N.2    Karmik, S.R.3
  • 23
    • 56049106112 scopus 로고    scopus 로고
    • The experimental investigation of the effects of uncoated, PVD and CVD coated cemented carbide inserts and cutting parameters on surface roughness in CNC turning and its prediction using artificial neural networks
    • M. Nalbant, H. Gokkaya, I. Toktas, and G. Sur The experimental investigation of the effects of uncoated, PVD and CVD coated cemented carbide inserts and cutting parameters on surface roughness in CNC turning and its prediction using artificial neural networks Robotics and Computer-Integrated Manufacturing 25 2009 211 223
    • (2009) Robotics and Computer-Integrated Manufacturing , vol.25 , pp. 211-223
    • Nalbant, M.1    Gokkaya, H.2    Toktas, I.3    Sur, G.4
  • 24
    • 75149120102 scopus 로고    scopus 로고
    • CNG-diesel engine performance and exhaust emission analysis with the aid of artificial neural network
    • T.F. Yusaf, D.R. Buttsworth, K.H. Saleh, and B.F. Yousif CNG-diesel engine performance and exhaust emission analysis with the aid of artificial neural network Applied Energy 87 2010 1661 1669
    • (2010) Applied Energy , vol.87 , pp. 1661-1669
    • Yusaf, T.F.1    Buttsworth, D.R.2    Saleh, K.H.3    Yousif, B.F.4
  • 25
    • 29244491457 scopus 로고    scopus 로고
    • Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a Diesel engine
    • A. Parlak, Y. Islamoglu, H. Yasar, and A. Egrisogut Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a Diesel engine Applied Thermal Engineering 26 2006 824 828
    • (2006) Applied Thermal Engineering , vol.26 , pp. 824-828
    • Parlak, A.1    Islamoglu, Y.2    Yasar, H.3    Egrisogut, A.4
  • 26
    • 58949083686 scopus 로고    scopus 로고
    • Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network
    • G. Najafi, B. Ghobadian, T. Tavakoli, D.R. Buttsworth, T.F. Yusaf, and M. Faizollahnejad Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network Applied Energy 86 2009 630 639
    • (2009) Applied Energy , vol.86 , pp. 630-639
    • Najafi, G.1    Ghobadian, B.2    Tavakoli, T.3    Buttsworth, D.R.4    Yusaf, T.F.5    Faizollahnejad, M.6
  • 27
    • 29744469216 scopus 로고    scopus 로고
    • Prediction of the distillation profile and cold properties of diesel fuels using mid-IR spectroscopy and neural networks
    • N. Pasadakis, S. Sourligas, and Ch Foteinopoulos Prediction of the distillation profile and cold properties of diesel fuels using mid-IR spectroscopy and neural networks Fuel 85 2006 1131 1137
    • (2006) Fuel , vol.85 , pp. 1131-1137
    • Pasadakis, N.1    Sourligas, S.2    Foteinopoulos, C.3
  • 28
    • 34948899802 scopus 로고    scopus 로고
    • Artificial neural network approaches on composition-property relationships of jet fuels based on GC-MS
    • G. Liu, L. Wang, H. Qu, H. Shen, X. Zhang, and S. Zhang Artificial neural network approaches on composition-property relationships of jet fuels based on GC-MS Fuel 86 2007 2551 2559
    • (2007) Fuel , vol.86 , pp. 2551-2559
    • Liu, G.1    Wang, L.2    Qu, H.3    Shen, H.4    Zhang, X.5    Zhang, S.6
  • 29
    • 44149097594 scopus 로고    scopus 로고
    • Application of artificial neural networks to predict chemical desulfurization of Tabas coal
    • E. Jorjani, S.C. Chelgani, and Mesroghli Sh Application of artificial neural networks to predict chemical desulfurization of Tabas coal Fuel 87 2008 2727 2734
    • (2008) Fuel , vol.87 , pp. 2727-2734
    • Jorjani, E.1    Chelgani, S.C.2    Sh, M.3
  • 30
    • 5044252688 scopus 로고    scopus 로고
    • A diesel engine's performance and exhaust emissions
    • E. Arcaklioglu, and I. Celikten A diesel engine's performance and exhaust emissions Applied Energy 80 2005 11 22
    • (2005) Applied Energy , vol.80 , pp. 11-22
    • Arcaklioglu, E.1    Celikten, I.2
  • 32
    • 78651467913 scopus 로고    scopus 로고
    • Prediction of diesel engine performance using biofuels with artificial neural network
    • H. Oguz, I. Saritas, and H.E. Baydan Prediction of diesel engine performance using biofuels with artificial neural network Expert Systems with Applications 37 2010 6579 6586
    • (2010) Expert Systems with Applications , vol.37 , pp. 6579-6586
    • Oguz, H.1    Saritas, I.2    Baydan, H.E.3
  • 33
    • 71749087451 scopus 로고    scopus 로고
    • Prediction of surface roughness in the end milling machining using artificial neural network
    • Z. Azlan Mohd, H. Habibollah, and S. Safian Prediction of surface roughness in the end milling machining using artificial neural network Expert Systems with Applications 37 2010 1755 1768
    • (2010) Expert Systems with Applications , vol.37 , pp. 1755-1768
    • Azlan Mohd, Z.1    Habibollah, H.2    Safian, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.