[[1] AAAM, 1985. Abbreviated Injury Scale 1985. Des Plaines IL: Association for the Advancement of Automotive Medicine.]Search in Google Scholar
[[2] Abdel-Aty M.A., Abdelwahab H.T., 2004. Predicting injury severity levels in traffic crashes: a modeling comparison, Journal of Transportation Engineering, vol. 130, pp. 204-210.10.1061/(ASCE)0733-947X(2004)130:2(204)]Search in Google Scholar
[[3] Abdelwahab, H.T., Abdel-Aty, M.A., 2001. Development of artificial neural network models to predict driver injury severity in traffic accidents at signalizes, Intersection Transportation Research Record issue 1746, pp. 6-13.10.3141/1746-02]Search in Google Scholar
[[4] Akaike, H., 1974. A new look at the statistical model identification, IEEE Transactions on Automatic Control 19(6): 716-72310.1109/TAC.1974.1100705]Search in Google Scholar
[[5] Akaike Hirotugu, 1980. Likelihood and the Bayes procedure, in Bernardo, J. M.; et al., Bayesian Statistics, Valencia: University Press, pp. 143-166.]Search in Google Scholar
[[6] Baker S.P., O’Neill B., Haddon Jr W., Long W.B., 1974. The Injury Severity Score: a method for describing patients with multiple injuries and evaluating emergency care, The Journal of Trauma (LippincottWilliams &Wilkins), vol. 14, pp. 187-196.10.1097/00005373-197403000-00001]Search in Google Scholar
[[7] Beshah T., Ejigu D., Kromer P., Snasel V., Platos J., Abraham A., 2012. Learning the Classification of Traffic Accident Types, Fourth International Conference on Intelligent Networking and Collaborative Systems, Bucharest, Romania, September 19th-21st, 2012, pp. 463-468.10.1109/iNCoS.2012.75]Search in Google Scholar
[[8] Breiman L., Friedman J.H., Olshen R.A., Stone, C.J., 1984. Classification and regression trees. Monterey, CA: Wadsworth & Brooks/Cole Advanced Books & Software.]Search in Google Scholar
[[9] Breiman Leo, 1996. Bagging predictors. Machine Learning 24(2): 123-140.10.1007/BF00058655]Search in Google Scholar
[[10] Breiman, Leo., 1998 Arcing classifiers, The Annals of Statistics, vol. 26, pp.801-849.10.1214/aos/1024691079]Search in Google Scholar
[[11] Breiman Leo., 2001 Random Forests. Machine Learning, volume 45, pp.5-32.10.1023/A:1010933404324]Search in Google Scholar
[[12] Catell, R.B., 1966. The scree test for the number of factors. Multivariate Behavioral Research, 1,245-27610.1207/s15327906mbr0102_1026828106]Search in Google Scholar
[[13] Chang, L-.Y,Wang H.-W., 2006. Analysis of traffic injury severity: An application of non-parametric classification tree techniques, Accident Analysis and Prevention, vol. 38, pp. 1019-1027.10.1016/j.aap.2006.04.00916735022]Search in Google Scholar
[[14] Chang L.Y., Chien J.-T, 2013 Analysis of driver injury severity in truck-involved accidents using a non-parametric classification tree-model, Safety Science, vol. 51, pp. 17-22.10.1016/j.ssci.2012.06.017]Search in Google Scholar
[[15] Chong M.M., Abraham A., Paprzycki M., 2004. Traffic accident analysis using decision trees and neural networks, IADIS International Conference on Applied Computing, Portugal, IADIS Press, Pedro Isaias et al. (Eds.), ISBN: 9729894736, Vol. 2, pp. 39-42.]Search in Google Scholar
[[16] Delen D., Sharda R., Bessonov M., 2006. Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks, Accident Analysis and Prevention, vol. 38, pp. 434-444.10.1016/j.aap.2005.06.02416337137]Search in Google Scholar
[[17] Devijver P.A., Kittler J. 1982. Pattern Recognition: A Statistical Approach, Prentice-Hall, London, U.K.]Search in Google Scholar
[[18] Fx GarcL, Miguel GarcTorres, BeleliBatista, Jos Moreno-Pz, J. Marcos Moreno-Vega: Solving feature subset selection problem by a Parallel Scatter Search. European Journal of Operational Research 169(2): 477-489 (2006)10.1016/j.ejor.2004.08.010]Search in Google Scholar
[[19] Fisher, R. A., 1936. The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics 7 (2): 179-188.10.1111/j.1469-1809.1936.tb02137.x]Search in Google Scholar
[[20] Gini C., 1909. Concentration and dependency ratios (in Italian). English translation in Rivista di Politica Economica, 87 (1997), 769-789.]Search in Google Scholar
[[21] Gini C., 1912. ”Italian: VariabilitutabilitVariability and Mutability’, C. Cuppini, Bologna, 156 pages. Reprinted in Memorie di metodologica statistica (Ed. Pizetti E, Salvemini, T). Rome: Libreria Eredi Virgilio Veschi (1955).]Search in Google Scholar
[[22] Glover F., 1977. Heuristics for integer programming using surrogate constraints. Decision Sciences, vol. 8, pp. 156-166.10.1111/j.1540-5915.1977.tb01074.x]Search in Google Scholar
[[23] Goodman, SN 1999. Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy. Annals of Internal Medicine 130: 995-100410.7326/0003-4819-130-12-199906150-0000810383371]Search in Google Scholar
[[24] Grossberg S., 1987. Competitive learning: from interactive activation to adaptive resonance, Cognitive Science, vol. 11, pp. 23-63.10.1111/j.1551-6708.1987.tb00862.x]Search in Google Scholar
[[25] Hall M. A., 1998. Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand]Search in Google Scholar
[[26] Hall Mark, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten 2009; The WEKA Data Mining Software: An Update; SIGKDD Explorations, Volume 11, Issue 1.10.1145/1656274.1656278]Search in Google Scholar
[[27] Hardin J., Hilbe J., 2007. Generalized Linear Models and Extensions (2nd edition). College Station: Stata Press.]Search in Google Scholar
[[28] Haykin S., 1999. Neural Networks: A Comprehensive Foundation (2nd Edition), Prentice-Hall, Upper Saddle River, NJ.]Search in Google Scholar
[[29] Heckerman D. 1997. Bayesian Networks for Data Mining. Data Mining and Knowledge discovery, 1(1) : 79-119, 1997.]Search in Google Scholar
[[30] Kaiser, H. F., 1960 The application of electronic computer to factor analysis. Educational and Psychological Measurement, 20, 141-151.10.1177/001316446002000116]Search in Google Scholar
[[31] Khattak A., Rocha M., 2003. Are SUVs “supremely unsafe vehicles”? Analysis of rollovers and injuries with sport utility vehicles, Transportation Research Record 1840, pp. 167-177.10.3141/1840-19]Search in Google Scholar
[[32] Kohavi R., John G. H., 1997. Wrappers for feature subset selection, Artificial Intelligence 97 (1-2) 273-32410.1016/S0004-3702(97)00043-X]Search in Google Scholar
[[33] Langley P., Iba W., Thompson K., 1992. An analysis of Bayesian Classifiers. In Proc. Of the 10th National Conf. on Artificial Intelligence, pages 223-228.]Search in Google Scholar
[[34] Liu H., Setiono R., 1996. A probabilistic approach to feature selection - A filter solution. In: 13th International Conference on Machine Learning, 319-327]Search in Google Scholar
[[35] Ma J., Kockelman KM., Damien P. 2008 A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods. Accident Analysis and Prevention 40:964-975 (2008).10.1016/j.aap.2007.11.002]Search in Google Scholar
[[36] McCullagh P., Nelder J., 1989. Generalized Linear Models, London: Chapman and Hall, London, U.K.10.1007/978-1-4899-3242-6]Search in Google Scholar
[[37] MCMVTAR 1976 Manual on Classification of Motor Vehicle Traffic Accidents-Revision of 016.11970, Third Edition, National Safety Council, Chicago, Illinois, 1976.]Search in Google Scholar
[[38] Milton Jc, Shankar Vn, FL Mannering Fl Highway accident severities and the mixed logit model: An exploratory empirical analysis Accident Analysis & Prevention 40 (??), 260-26610.1016/j.aap.2007.06.006]Search in Google Scholar
[[39] Molina L.C., Belanche L., and Nebot A., 2002. Feature Selection Algorithms: A survey and Experimental Evaluation. In Proc. Of the 2002 IEEE Intl. Conf. on Data Mining.]Search in Google Scholar
[[40] Mujalli R.O., J. de Ona, 2012. Injury severity models for motor vehicle accidents: a review, Proceedings of the ICE - Transport, vol. 166, pp. 255-270.10.1680/tran.11.00026]Search in Google Scholar
[[41] Mussone L., Ferrari A., Oneta M., 1999. An analysis of urban collisions using an artificial intelligence model, Accident Analysis and Prevention, vol. 31, pp. 705-718.10.1016/S0001-4575(99)00031-7]Search in Google Scholar
[[42] Pearson, K., 1901. On Lines and Planes of Closest Fit to Systems of Points in Space. Philosophical Magazine, vol. 2, pp 559-572.10.1080/14786440109462720]Search in Google Scholar
[[43] Popkin C.L., Campbell B.J. Hansen A.R., and Stewart J.R., 1991. Analysis of the accuracy of the existing KABCO injury scale, Chapel Hill, NC: University of North Carolina Highway Safety Research Center e-archives scan.]Search in Google Scholar
[[44] Quddus M.A., Ison S.G., 2011. Predicting accident frequency at their severity levels and its application in site ranking using a two-stage mixed multivariate model, Accident Analysis & Prevention, vol. 43, pp. 1979-1990.10.1016/j.aap.2011.05.016]Search in Google Scholar
[[45] Quinlan, J. R., 1986. Induction of Decision Trees. Machine Learning 1: 81-106, Kluwer Academic Publishers.10.1007/BF00116251]Search in Google Scholar
[[46] Quinlan, J. R.,1993 C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA, 1993.]Search in Google Scholar
[[47] Ramoni M., and Sebastiani P., 2001. Robust Bayes Classifier. Artificial Intelligence, 125: 209-226 10.1016/S0004-3702(00)00085-0]Search in Google Scholar
[[48] Rezaie Moghaddam F., Afandizadeh Sh., Ziyadi M., 2011. Prediction of accident severity using artificial neural networks, International Journal of Civil Engineering, vol. 9,pp. 41-49.]Search in Google Scholar
[[49] Rumelhart D.E., Hinton G.E.,Williams R. J., 1986. Learning internal representations by error propagation, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1: Foundations, Rumelhart D.E., McClelland J.L., and the PDP research group. (eds), MIT Press, 1986]Search in Google Scholar
[[50] Savolainen, P.T., Mannering, F.L., Lord, D., and M.A. Quddus, 2011. “The Statistical Analysis of Highway Crash-Injury Severities: A Review and Assessment of Methodological Alternatives”, Accident Analysis and Prevention, Vol. 43, No. 5, 2011, pp. 1666-1676.10.1016/j.aap.2011.03.025]Search in Google Scholar
[[51] Schwarz, Gideon E. 1978. Estimating the dimension of a model. Annals of Statistics 6 (2): 461-46410.1214/aos/1176344136]Search in Google Scholar
[[52] Shanthi S., Geetha Ramani, 2012. Feature relevance analysis and classification of road traffic accident data through data mining techniques, Proceedings of the World Congress on Engineering and Computer Science (WCECS 2012), October 24th-26th, 2012, San Francisco, U.S.A., Vol I, pp. 122-127.]Search in Google Scholar
[[53] Shanti S., Geetha Ramani, 2012. Vehicle Safety Device (Airbag) Specific Classification of Road Traffic Accident Patterns through Data Mining Techniques. ACITY (2) 2012: 433-44310.1007/978-3-642-31552-7_45]Search in Google Scholar
[[54] Sohn, S.Y., Shin, H.W., 2001. Data mining for road traffic accident type classification, Ergonomics, vol. 44, pp. 107-117.10.1080/00140130120928]Search in Google Scholar
[[55] Sohn S.Y., Lee S.H., 2003. Data fusion, ensemble and clustering to improve the classification accuracy for the severity of road traffic accidents in Korea, Safety Science, vol. 41, pp. 1-14.10.1016/S0925-7535(01)00032-7]Search in Google Scholar
[[56] Spearman C., 1904. General Intelligence, objectively determined and measured. Am J Psychol 15:202-93.10.2307/1412107]Search in Google Scholar
[[57] Specht D. 1998. Probabilistic neural networks for classification, mapping, and associative memory, in Proceedings of the IEEE International Conference on Neural Networks, New York, U.S.A, pp. 525-532 (vol. 1).]Search in Google Scholar
[[58] Tambouratzis Tatiana, Souliou Dora, Chalikias Miltiadis S., Gregoriades Andreas: Combining probabilistic neural networks and decision trees for maximally accurate and efficient accident prediction. IJCNN 2010: 1-810.1109/IJCNN.2010.5596610]Search in Google Scholar
[[59] Tavakoli Kashani A., Shariat-Mohaymany A., Ranjbari A., 2012. Analysis of factors associated with traffic injury severity on rural roads in Iran, Journal of Injury and Violence Research, vol. 4, pp. 36-4110.5249/jivr.v4i1.67329127921502788]Search in Google Scholar
[[60] Vilalta R., Drissi Y., A perspective view and survey of meta-learning, Artificial Intelligence Review, VOL. 18, PP. 77-95, 200210.1023/A:1019956318069]Search in Google Scholar
[[61] Wang C., Quddus M.A., Ison S.G., 2011. Predicting accident frequency at their severity levels and its application in site ranking using a two-stage mixed multivariate model, Accident Analysis & Prevention, vol. 43, pp.1979-199010.1016/j.aap.2011.05.01621819826]Search in Google Scholar
[[62] Worku Y.M., Deogratias E., Deo C., Maher Q. 2013, Exploring factors contributing to injury severity at freeway merging and diverging locations in Ohio. Accident Analysis & Prevention Volume 55, June 2013, Pages 202-21010.1016/j.aap.2013.03.008]Search in Google Scholar
[[63] Zadeh, L.A., 1965. Fuzzy sets, Information and Control, vol. 8, pp. 338-353 10.1016/S0019-9958(65)90241-X]Search in Google Scholar