Performance Evaluation of 14 Neural Network Architectures Used for Predicting Heat Transfer Characteristics of Engine Oils

REFERENCES

• Abou-Ziyan , H. 2004 . Heat Transfer Characteristics of Some Oils used for Engine Cooling . Energy Conversion and Management , 45 : 2553 – 2569 .
   Web of Science ®Google Scholar
• Lee , B. , Kim , J. and Kwon , D. 2003 . Stress–strain Curves of Flipchip Solder Balls Based on Finite-element Modeling of Thermal Displacements Measured by Electronic Speckle Pattern Interferometry . J. Electron. Mater. , 32 ( no. 11 ) : 1322 – 1329 .
   Web of Science ®Google Scholar
• Mittal and Zhang , J. 2001 . Artifical Neural Network for the Prediction of Temperature, Moisture and Fat Contents in Metal Balls During Deep-fat Frying . I. J. Food Science and Technology , 36 : 489 – 497 .
   Web of Science ®Google Scholar
• Tam , H. , Tam , S. , Ghajar , A. and Tam , L. 2006 . Factor Analysis of Convective Heat Transfer for a Horizontal Tube in Turbulent Flow Region Using Artificial Neural Network . Computationl Methods in Engineering and Science , EPMESC X, Sanya, Hainan, China
   Google Scholar
• Sablani , S. , Kacimov , A. , Perret , J. , Mujumdar , A. and Campo , A. 2005 . Non-iterative Estimation of Heat Transfer Coefficients Using Artificial Neural Network Models . International Journal of Heat and Mass Transfer , 48 ( no. 3–4 ) : 665 – 679 .
   Web of Science ®Google Scholar
• Wu , J. and Su , G. 2007 . Prediction of Flow Boiling Curves Based on Artificial Neural Network . Yuanzineng Kexue Jishu/Atomic Energy Science and Technology , 41 ( no. 3 ) : 315 – 320 .
   Google Scholar
• Metin , E. 2006 . Prediction of the Pool Boiling Critical Heat Flux Using Artificial Neural Network . IEEE Transactions on Components and Packaging Technologies , 29 ( no. 4 ) : 770 – 777 .
   Web of Science ®Google Scholar
• Wang , W. , Zhao , L. and Zhang , C. 2006 . Generalized Neural Network Correlation for Flow Boiling Heat Transfer of R22 and its Alternative Refrigerants Inside Horizontal Smooth Tubes . International Journal of Heat and Mass Transfer , 49 ( no. 15–16 ) : 2458 – 2465 .
   Web of Science ®Google Scholar
• Su , G. , Fukuda , K. , Morita , K. , Pidduck , M. , Jia , D. , Matsumoto , T. and Akasaka , R. 2002 . Applications of Artificial Neural Network for the Prediction of Flow Boiling Curves . Journal of Nuclear Science and Technology , 39 ( no. 11 ) : 1190 – 1198 .
   Web of Science ®Google Scholar
• Manickaraj , J. and Balasubramanian , N. 2008 . Estimation of the Heat Transfer Coefficient in a Liquid-solid Fluidized Bed Using an Artificial Neural Network . Advanced Powder Technology , 19 ( no. 2 ) : 119 – 130 .
   Web of Science ®Google Scholar
• Dudul , S. V. 2007 . Identification of a Liquid Saturated Steam Heat Exchanger Using Focused Time Lagged Recurrent Neural Network Model . IETE Journal of Research , 53 ( no. 1 ) : 69 – 82 .
   Web of Science ®Google Scholar
• Markowski , M. , Korzybski , P. and Urbaniec , K. Neural Network Assisted On-line Cleaning of Heat Exchanger Network . Proc. 17th International Congress of Chemical and Process Engineering . Prague , Czech Republic.
   Google Scholar
• Jalili-Kharaajoo , M. 2005 . Neural Network Control of Heat Exchanger Plant, Proc. 2nd International Symposium on Neural Networks: Advances in Neural Networks - ISSN , China : Chongqing .
   Google Scholar
• Ermis , K. , Erek , A. and Dincer , I. 2007 . Heat Transfer Analysis of Phase Change Process in a Finned-tube Thermal Energy Storage System Using Artificial Neural Metwork . International Journal of Heat and Mass Transfer , 50 ( no. 5–16 ) : 3163 – 3175 .
   Web of Science ®Google Scholar
• Arcaklioglu , E. , Erisen , A. and Yilmaz , R. 2004 . Artificial Neural Network Analysis of Heat Pumps Using Refrigerant Mixtures . Energy Conversion and Management , 45 ( no. 11–12 ) : 1917 – 1929 .
   Web of Science ®Google Scholar
• Cui , X. , Weng , J. and Groll , M. 2003 . Heat Transfer Performance Model of Pulsating Heat Pipe Based on Neural Network . Huagong Xuebao/Journal of Chemical Industry and Engineering (China) , 54 ( no. 9 ) : 1319 – 1322 .
   Google Scholar
• Boccaletti , C. , Cerri , G. and Seyedan , B. 2001 . A Neural Network Simulator of a Gas Turbine with a Waste Heat Recovery Section . Journal of Engineering for Gas Turbines and Power , 123 ( no. 2 ) : 371 – 376 .
   Web of Science ®Google Scholar
• Ward Systems Group Inc. 2009 . Neuroshell-2 Manual Frederick , , MD, USA
   Google Scholar
• Mahmoud , M. A. and Abu Kiefa , M. 1999 . Neural Network Solution of the Inverse Vibration Problem . NDT & E International , 32 ( no. 2 ) : 91 – 99 .
   Web of Science ®Google Scholar
• Elmeshaiei , E. A. , Orabi , S. and Mahmoud , M. A. Tool Wear Prediction Approach for Turning Operations Based on General Regression Neural Network Technique . Proc. 4th Conference on Advanced Computation in Design and Manufacturing, . Bristol , UK.
   Google Scholar
• Ben-Nakhi , A. and Mahmoud , M. A. 2002 . Energy Conservation in Buildings through Efficient A/C Control Using Neural Networks . Applied Energy , 73 : 5 – 23 .
   Web of Science ®Google Scholar
• Ben-Nakhi , A. and Mahmoud , M. A . 2004 . Cooling Load Prediction for Buildings Using General Regression Neural Networks . Energy Conversion and Management , 45 ( no. 13–14 ) : 2127 – 2141 .
   Web of Science ®Google Scholar
• Mahmoud , M. A. and Ben-Nakhi , A. 2007 . Neural Networks Analysis of Free Laminar Convection Heat Transfer in a Partitioned Enclosure . Communications in Nonlinear Science and Numerical Simulation , 12 ( no. 7 ) : 1265 – 1276 .
   Google Scholar
• Specht , D. F. 1991 . A General Regression Neural Network . IEEE Trans Neural Networks , 2 ( no. 6 ) : 568 – 576 .
   PubMed Web of Science ®Google Scholar
• Kreyszig , E. 1993 . Advanced Engineering Mathematics , 7th ed. , New York : Wiley .
   Google Scholar
• Farlow , S. J. , ed. 1984 . Self-organizing Method in Modeling: GMDH Type Algorithms , 54 Marcel Dekker Inc., NY, USA : Statistics: Textbooks and Monographs .
   Google Scholar
• Mahmoud , M. A. and Ben-Nakhi , A. 2003 . Architecture and Performance of Neural Networks for Efficient A/C Control in Buildings . Energy Conversion and Management , 44 ( no. 20 ) : 3207 – 3226 .
   Web of Science ®Google Scholar
• Tabachnick , B. G. and Fidell , L. S. 1996 . Using Multivariate Statistics , 3rd ed. , New York : Harper Collins .
   Google Scholar
• Wheeler , D. 2004 . Advanced Topics in Statistical Process Control , 2nd ed. , SPC Press, Knoxville, TN, USA : Statistical Process Control .
   Google Scholar