[1] V. Kodur and M. Naser, “Importance factor for design of bridges against fire hazard,” Engineering Structure, vol. 54, no. 1, pp. 207-220, 2013.
[2] M. Garlock, I. Paya-Zaforteza, V. Kodur and L. Gu, “Fire hazard in bridges: Review, assessment and repair strategies,” Engineering Structure, vol. 35, no. 1, pp. 89- 98, 2012.
[3] W. Wang, R. Liu and B. Wu, “Analysis of a bridge collapsed by an accidental blast loads,” Engineering Failure Analysis, vol. 36, no. 1, pp. 353-361, 2014.
[4] M. Bielli, “A DSS approach to urban traffic management,” European Journal of Operational Research, vol. 61, no. 1-2, pp. 106-113,, 1992.
[5] R. Asadi and M. Ghatee, “A rule-based decision support system in intelligent Hazmat transportation system,” IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 5, pp. 2756-2764, 2015.
[6] K. Zografos, K. Androutsopoulos and G. Vasilakis, “A real-time decision support system for roadway network incident response logistics,” Transportation Research Part C: Emerging Technologies, vol. 10, no. 1, pp. 1-18, 2002.
[7] B. Yanev, “The management of bridges in New York City,” Engineering Structure, vol. 20, no. 11, pp. 1020-1026, 1998.
[8] R. Klashner and S. Sabet, “A DSS Design Model for complex problems: Lessons from mission critical infrastructure,” Decision Support System, vol. 43, no. 3, pp. 990-1013, 2007.
[9] S. Yehia, O. Abudayyeh, I. Fazal and D. Randolphc, “A decision support system for concrete bridge deck maintenance,” Advance Engineering Software, vol. 39, no. 3, pp. 202-210, 2008.
[10] S. Abpeykar and M. Ghatee, “Supervised and unsupervised learning DSS for incident management in intelligent tunnel: A case study in Tehran Niayesh tunnel,” Tunnelling and Underground Space Technology, vol. 42, pp. 293-306, 2014.
[11] E. Abbasi, M. E. Shiri and M. Ghatee, “A regularized root–quartic mixture of experts for complex classification problems,” Knowledge-Based Systems, vol. 110, pp. 98-109, 2016.
[12] H. Eftekhari and M. Ghatee, “An inference engine for smartphones to preprocess data and detect stationary and transportation modes,” Transportation Research Part C: Emerging Technologies, vol. 69, pp. 313-327, 2016.
[13] M. M. Bejani and M. Ghatee, “A context aware system for driving style evaluation by an ensemble learning on smartphone sensors data,” Transportation Research Part C: Emerging Technologies, vol. 89, pp. 303-320, 2018.
[14] J. Lu, S. Chen, W. Wang and H. Zuylen, “A hybrid model of partial least squares and neural network for traffic incident detection,” Expert Systems with Application, vol. 39, no. 5, pp. 4775-4784, 2012.
[15] D. Srinivasan, X. Jin and R. Cheu, “Adaptive neural network models for automatic incident detection on freeways,” Neurocomputing, vol. 64, no. 1, pp. 473-469, 2005.
[16] S. Che and W. Wang, “Decision tree learning for freeway automatic incident detection,” Expert System with Application, vol. 36, no. 2, pp. 4101-4105, 2009.
[17] J. Abellán, G. López and J. Oña, “Analysis of traffic accident severity using Decision Rules via Decision Trees,” Expert System with Application, vol. 40, no. 15, pp. 6047- 6054, 2013.
[18] W. Yeung and J. Smith, “Damage detection in bridges using neural networks for pattern recognition of vibration signatures,” Engineering Structure, vol. 27, no. 5, pp. 685-698, 2005.
[19] P. Chen, H. Shen, C. Lei and L. Chang, “Support-vector-machine-based method for automated steel bridge rust assessment,” Automation in Construction, vol. 23, no. 1, p. 9–19, 2012.
[20] E. Abbasi, M. Shiri and M. Ghatee, “A regularized root–quartic mixture of experts for complex classification problems,” Knowledge-Based Systems, vol. 110, pp. 98-109, 2016.
[21] S. Abpeykar and M. Ghatee, “An ensemble of RBF neural networks in decision tree structure with knowledge transferring to accelerate multi-classification,” Neural Computing and Applications, vol. in press, pp. 1-21, 2018.
[22] S. Abpeykar and M. Ghatee, “Decent direction methods on the feasible region recognized by supervised learning metamodels to solve unstructured problems,” Journal of Information and Optimization Sciences, vol. in press, pp. 1-18, 2018.
[23] M. Georgiopoulos, C. Li and T. Kocak, “Learning in the feed-forward random neural network: A critical review,” Performance Evaluation, vol. 68, no. 4, pp. 361- 384, 2011.
[24] P. Pumpuang, A. Srivihok and P. Praneetpolgrang, “Comparisons of classifier algorithms: Bayesian network, C4.5, decision forest and NB tree for course registration planning model of undergraduate students,” Singapore, 2008.
[25] L. Bel, D. Allard, J. Laurent, C. R. and B.-H. A., “CART algorithm for spatial data: application to environmental and ecological data,” Computational Statistics & Data Analysis, vol. 53, no. 8, p. 3082–3093, 2009.
[26] S. Crawford, “Extensions to the CART algorithm,” International Journal of Man-Machine Studies, vol. 31, no. 2, p. 197–217, 1989.
[27] C. Hsu, Y. Huang and K. Chang, “Extended Naive Bayes classifier for mixed data,” Expert Systems with Applications, vol. 35 , no. 3, p. 1080–1083, 2008.
[28] L. Koc, T. Mazzuchi and S. Sarkani, “A network intrusion detection system based on a Hidden Naive Bayes multiclass classifier,” Expert Systems with Applications, vol. 39, no. 18, p. 13492–13500, 2012.
[29] S. Mahdevari, H. Haghighat and S. Torabi, “A dynamically approach based on SVM algorithm for prediction of tunnel convergence during excavation,” Tunnelling and Underground Space Technology, vol. 38, no. 1, p. 59–68, 2013.
[30] T. K. Moon, “The expectation-maximization algorithm,” IEEE Signal processing magazine, vol. 13, no. 6, pp. 47-60, 1996.
[31] A. Ahmad and L. Dey, “A k-mean clustering algorithm for mixed numeric and categorical data,” Data & Knowledge Engineering, vol. 63, no. 2, pp. 503-527, 2007.
[32] M. Panda and M. Patra, “A Novel classification via clustering method for anomaly based network intrusion detection system,” International Journal of Network Security, vol. 1, no. 2, p. 17–22, 2010.
[33] M. Blachnik and W. Duch, “LVQ algorithm with instance weighting for generation of prototype-based rules,” Neural Networks, vol. 24, no. 8, p. 824–830, 2011.
[34] Pallavi and S. Godara, “A comparative performance analysis of clustering algorithms,” International Journal of Engineering Research and Applications, vol. 1, no. 3, p. 441–445, 2011.
[35] M. Kiang, D. Fisher, J. Chen, S. Fisherd and R. Chia, “The application of SOM as a decision support tool to identify AACSB peer schools,” Decision Support System, vol. 47, no. 1, p. 51–59, 2009.
[36] Z. Feng and T. Xu, “Comparison of SOM and PCA-SOM in fault diagnosis of ground-testing bed,” Procedia Engineering, vol. 15, no. 1, p. 1271–1276, 2011.
[37] K. Zografos, G. Vasilakis and I. Giannouli, “Methodological framework for developing decision support systems (DSS) for hazardous materials emergency response operations,” Journal of Hazardous Materials, vol. 71, no. 1-3, pp. 503- 521, 2000.
[38] T. Guimaraes, “DSS for top executives: Obstacles and bridges,” International Journal of Information Management, vol. 7, no. 1, pp. 21-35, 1987.
[39] L. Young, “Decision support systems for workers: A bridge to advancing productivity,” Information Management, vol. 16, no. 3, pp. 131- 140, 1989.
[40] X. Song, W. Chen, Y. Chen and B. Jiang, “Candidate working set strategy based sequential minimal optimization algorithm in support vector machine,” Information Processing & Management, vol. 45, no. 5, p. 584–592, 2009.
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