This study attempts to present the artificial intelligence and fuzzy logic methodology to investigate the stability of jointed rock slopes based on slope mass rating (SMR) in open-pit mining projects in Khoy, West Azerbaijan, Iran. As methodology, the coupled procedure based on SMR and fuzzy logic (named FSMR) was used to quantification and classification of 25 excavated mine slopes where applied on 6 openpit mines in Khoy region. For this purpose, the slopes conditions have been evaluated during field surveys and provide the input information for initial SMR model. The fuzzy model has been used to improve the results as well as reduced errors in field evaluations so that it can produce results with higher accuracy. As a result of the presented article, the modified method provides high accurate results in lower evaluating time. پرونده مقاله

The presented article tried to utilize the empirical rock mass classifications to rock mass quantification and stability analysis for several open-pit mining projects in Khoy, West-Azerbaijan, NW of Iran. For this purpose, the geomechanical classifications including rock mass rating (RMR), slope mass rating (SMR), and Qslope have been used. The study aim is provide the quick assessment by considering these classifications to appropriate mines design and stability analysis which implemented on 20 open-pit mining cases in Khoy. Based on the results, it has been determined that most slopes are in the generally stable class, but some of the slopes show unstable conditions which stabilization is necessary. In the meantime, one slope is in an unfavorable condition. پرونده مقاله