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Comparative study of artificial neural network and statistical models for predicting student grade point averages

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  • Gorr, Wilpen L.
  • Nagin, Daniel
  • Szczypula, Janusz

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  • Gorr, Wilpen L. & Nagin, Daniel & Szczypula, Janusz, 1994. "Comparative study of artificial neural network and statistical models for predicting student grade point averages," International Journal of Forecasting, Elsevier, vol. 10(1), pages 17-34, June.
    • Handle: RePEc:eee:intfor:v:10:y:1994:i:1:p:17-34
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    Cited by:

    1. Sen Cheong Kon & Lindsay W. Turner, 2005. "Neural Network Forecasting of Tourism Demand," Tourism Economics, , vol. 11(3), pages 301-328, September.
    2. Yiannis Anagnostopoulos, 2016. "Risk Pricing in Emerging Economies: Credit Scoring and Private Banking in Iran," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 5(1), pages 51-72, January.
    3. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Norbert Schanne, 2011. "Neural networks for regional employment forecasts: are the parameters relevant?," Journal of Geographical Systems, Springer, vol. 13(1), pages 67-85, March.
    4. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    5. Qi, Min & Yang, Sha, 2003. "Forecasting consumer credit card adoption: what can we learn about the utility function?," International Journal of Forecasting, Elsevier, vol. 19(1), pages 71-85.
    6. OlaOluwa S. Yaya & Ahamuefula E. Ogbonna & Fumitaka Furuoka & Luis A. Gil‐Alana, 2021. "A New Unit Root Test for Unemployment Hysteresis Based on the Autoregressive Neural Network," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 960-981, August.
    7. repec:dgr:vuarem:2009-14 is not listed on IDEAS
    8. Green, Kesten C. & Armstrong, J. Scott, 2015. "Simple versus complex forecasting: The evidence," Journal of Business Research, Elsevier, vol. 68(8), pages 1678-1685.
    9. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    10. Jun Kang & Hyun Jun Lee & Seung Hwan Jeong & Hee Soo Lee & Kyong Joo Oh, 2020. "Developing a Forecasting Model for Real Estate Auction Prices Using Artificial Intelligence," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    11. Chatfield, Chris, 1995. "Positive or negative?," International Journal of Forecasting, Elsevier, vol. 11(4), pages 501-502, December.
    12. Mostafa, Mohamed M. & El-Masry, Ahmed A., 2016. "Oil price forecasting using gene expression programming and artificial neural networks," Economic Modelling, Elsevier, vol. 54(C), pages 40-53.
    13. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    14. Yaya, OlaOluwa S & Ogbonna, Ephraim A & Furuoka, Fumitaka & Gil-Alana, Luis A., 2019. "A new unit root analysis for testing hysteresis in unemployment," MPRA Paper 96621, University Library of Munich, Germany.
    15. Adil Korchi & Fayçal Messaoudi & Ahmed Abatal & Youness Manzali, 2023. "Machine Learning and Deep Learning-Based Students’ Grade Prediction," SN Operations Research Forum, Springer, vol. 4(4), pages 1-21, December.
    16. Caulkins, Jonathan & Cohen, Jacqueline & Gorr, Wilpen & Wei, Jifa, 1996. "Predicting criminal recidivism: A comparison of neural network models with statistical methods," Journal of Criminal Justice, Elsevier, vol. 24(3), pages 227-240.
    17. Shiva Moslemi & Abolfazl Mirzazadeh & Gerhard-Wilhelm Weber & Mohammad Ali Sobhanallahi, 2022. "Integration of neural network and AP-NDEA model for performance evaluation of sustainable pharmaceutical supply chain," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 1116-1157, September.
    18. Mostafa, Mohamed M. & Nataraajan, Rajan, 2009. "A neuro-computational intelligence analysis of the ecological footprint of nations," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3516-3531, July.
    19. Curry, B. & Morgan, P.H., 2006. "Model selection in Neural Networks: Some difficulties," European Journal of Operational Research, Elsevier, vol. 170(2), pages 567-577, April.
    20. Richards, Timothy J. & Patterson, Paul M. & van Ispelen, Pieter, 1998. "Modeling Fresh Tomato Marketing Margins: Econometrics And Neural Networks," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 27(2), pages 1-14, October.
    21. H. Zhang & T.Q. Song & K.L. Wang & G.X. Wang & H. Hu & F.P. Zeng, 2012. "Prediction of crude protein content in rice grain with canopy spectral reflectance," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 58(11), pages 514-520.
    22. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2004. "Vector autoregressive models versus neural networks in forecasting: an application to Euro-inflation and divisia money," Money Macro and Finance (MMF) Research Group Conference 2003 5, Money Macro and Finance Research Group.
    23. Gruca, TS & Klemz, BR, 1998. "Using Neural Networks to Identify Competitive Market Structures from Aggregate Market Response Data," Omega, Elsevier, vol. 26(1), pages 49-62, February.
    24. Erol Eğrioğlu & Robert Fildes, 2022. "A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1355-1383, April.
    25. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.

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