Alizadeh, M.; alizadeh, E.; Asadollahpour Kotenaee, S.; Shahabi, H.; Beiranvand Pour, A.; Panahi, M.; Baharin Bin, A. and Lee, S., (2018), Social Vulnerability Assessment Using Artificial Neural Network (ANN) Model for Earthquake Hazard in Tabriz City, Iran, Sustainability, 10, 3376; doi:10.3390/su10103376.
Bradley, AP., (1997), the use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit.30: 1145-1159.
Chich-hao Wang, (2013), “Land-use allocation and earthquake damage mitigation: a combined spatial statistics and optimization approach“, presented in partial fulfillment of the requirements for the degree doctor of philosophy in the graduate school of the OHIO state university.
Duzgun, H. S. B., Yucemen, M. S., Kalaycioglu, H. S., Celik, K., Kemec, S., Ertugay, K., and Deniz, A. (2011), An integrated earthquake vulnerability assessment framework for urban areas. Natural Hazards, 59(2), 917–947. Doi: 10.1007/s11069-011-9808-6
Hanley, A and Mcneil, J., (1982), the meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 143: 29-36.
Ogie, R., I. and Pradhan, B, (2019), Natural Hazard and Social Vulnerability of Place: The Strength-Based Approach Applied to Wollongong, Australia. International Journal of Disaster Risk Science, volume 1: 404-420.
Zambon, M., R. Lawrence, A. Bunn, and S. Powell., (2006), Effect of alternative splitting rules on image processing using classification tree analysis. Photogrammetric Engineering and Remote Sensing, 72(1): 25–30.