. Malkani, M.S. and Mahmood, Z.A.F.A.R. (2016). Mineral resources of Pakistan: a review. Geological Survey of Pakistan, Record. 128: 1-90.
. Malkani, M.S. and Mahmood, Z. (2017). Mineral Resources of Pakistan: provinces and basins wise. Geological Survey of Pakistan, Memoir. 25: 1-179.
. Malkani, M.S., Mahmood, Z., Alyani, M.I. and Siraj, M. (2017). Mineral Resources of Khyber Pakhtunkhwa and FATA, Pakistan. Geological Survey of Pakistan, Information Release. 996: 1-61.
. kausar sultan shah, S.k., Abdur Rehman, Socio-Environmental Impacts of Coal Mining: A Case Study of Cherat Coal Mines Pakistan. Int. J. Econ. Environ. Geol. Vol., 2019. 10 (3): p. 129-133.
. Shah, K.S., Khan, M.A., Khan, S., Rahman, A., Khan, N.M. and Abbas, N. (2020). Analysis of Underground Mining Accidents at Cherat Coalfield, Pakistan. International Journal of Economic and Environmental Geology. 11 (1): 113-117.
. Jiskani, I. M., Cai, Q., Zhou, W. and Lu, X. (2020). Assessment of risks impeding sustainable mining in Pakistan using fuzzy synthetic evaluation. Resources Policy. 69: 101820.
. Jiskani, I.M., Ullah, B., Shah, K.S., Bacha, S., Shahani, N.M., Ali, M. and Qureshi, A.R. (2019). Overcoming mine safety crisis in Pakistan: An appraisal. Process safety progress. 38 (4): e12041.
. Jiskani, I.M., Cai, Q., Zhou, W., Chang, Z., Chalgri, S.R., Manda, E. and Lu, X. (2020). Distinctive Model of Mine Safety for Sustainable Mining in Pakistan. Mining, Metallurgy & Exploration, 1-15.
. Zhang, J., Fu, J., Hao, H., Fu, G., Nie, F. and Zhang, W. (2020). Root causes of coal mine accidents: Characteristics of safety culture deficiencies based on accident statistics. Process Safety and Environmental Protection, 136, 78-91.
. Shahani, N.M., Sajid, M.J., Jiskani, I.M., Ullah, B. and Qureshi, A.R. (2020). Comparative analysis of coal Miner’s fatalities by fuzzy logic. Journal of Mining and Environment.
. Bonsu, J., Van Dyk, W., Franzidis, J.P., Petersen, F. and Isafiade, A. (2017). A systemic study of mining accident causality: an analysis of 91 mining accidents from a platinum mine in South Africa. Journal of the Southern African Institute of Mining and Metallurgy. 117 (1): 59-66.
. Sarkar, S., Vinay, S., Raj, R., Maiti, J. and Mitra, P. (2019). Application of optimized machine learning techniques for prediction of occupational accidents. Computers & Operations Research, 106, 210-224.
. Wang, R., Xu, K., Xu, Y. and Wu, Y. (2020). Study on prediction model of hazardous chemical accidents. Journal of Loss Prevention in the Process Industries, 104183.
. Xie, X., Fu, G., Xue, Y., Zhao, Z., Chen, P., Lu, B. and Jiang, S. (2019). Risk prediction and factors risk analysis based on IFOA-GRNN and apriori algorithms: Application of artificial intelligence in accident prevention. Process Safety and Environmental Protection. 122: 169-184.
. Xu, Q. and Xu, K. (2020). Statistical analysis and prediction of fatal accidents in the metallurgical industry in China. International journal of environmental research and public health, 17 (11): 3790.
. Box, G.E., et al., Time series analysis: forecasting and control. 2015: John Wiley & Sons.
. Kher, A.A. and Yerpude, R. (2016). Application of Forecasting Models on Indian Coal Mining Fatal Accident (Time Series) Data. International Journal of Applied Engineering Research, 11(2), 1533-1537.
. Al-Zyood, M. (2017). Forecast car accident in Saudi Arabia with ARIMA models. International Journal of Soft Computing and Engineering, 7 (3): 30, 33.
. Li, Y. (2019). Analysis and Forecast of Global Civil Aviation Accidents for the Period 1942-2016. Mathematical Problems in Engineering, 2019.
. Ghédira, A., Kammoun, K. and Saad, C.B. (2018). Temporal Analysis of Road Accidents by ARIMA Model: Case of Tunisia. International Journal of Innovation and Applied Studies. 24 (4): 1544-1553.
. Rajaprasad, S.V.S. (2018). Prediction of fatal accidents in Indian factories based on ARIMA. Production Engineering Archives. 18 (18): 24-30.
. Wu, M., Ye, Y., Hu, N., Wang, Q., Jiang, H. and Li, W. (2020). EMD-GM-ARMA Model for Mining Safety Production Situation Prediction. Complexity.
. Shao, X., Boey, L.L. and Luo, Y. (2019). Traffic Accident Time Series Prediction Model Based on Combination of ARIMA and BP and SVM. Journal of Traffic and Logistics Engineering Vol, 7(2).
. Yixuan, S.U.N., Chunfu, S.H.A.O., Xun, J. I. and Liang, Z.H.U. (2015). Urban traffic accident time series prediction model based on combination of ARIMA and information granulation SVR. Journal of tsinghua university (science and technology). 54 (3): 348-353.
. Shumway, R. and D. Stoffer. (2011). ARIMA models’, Time Series Analysis and Its Applications. Springer New York, NY, USA.