fuzzy logic

In this work, we employ the fuzzy logic technique to achieve and present, for the first time, a proper analysis of the actual intensity of the increase in the coal miners’ fatality rates in Pakistan from 2010 to 2018, compared with China and India, with an objective to minimize the impact of incidents on the miners’ fatalities. The average and yearwise fatality rates in Pakistan, compared with China and India, are used for the fuzzy logic technique in order to calculate the actual degree of flexibility for the surging fatalities. The findings show that both the average (2010-2018) and yearwise fatality rates in 2011, 2015, and 2018 are 2.44, 1.74, and 1.6, respectively. In the fuzzy logic technique, the variables whose membership function (µ) values are ≥ 1 represent the absolute truth. The membership function values for the years 2011, 2015, and 2018 are alarmingly high for the fatalities of coal miners. Similarly, except for 2014 and 2010, where 0 represents the absolute falseness, the results for the remaining years indicate high fatality rates with a flexibility (or small extent) of its corresponding membership function (µ) values such as 0.623, 0.739, 0.219, 0.173 and 0.115, and 0.714, 0.24, 0.01, 0.324 and 0.317 using the average and yearwise analysis, respectively, compared with China. Likewise, the fuzzy logic membership function (µ) values compared with India in the remaining years are 0.704, 0.795, 0.386, 0.159, 0.352 and 0.306, and 0.675, 0.795, 0.386, 0.186, 0.321 and 0.322, respectively. The proposed fuzzy logic analysis has been founded based on the theory of fuzzy sets to properly identify the miners’ fatalities, and also to suggest the implementation of appropriate recommendations to reduce the fatalities in the coal mines in Pakistan.

One of the most widely used methods for the excavation of metro tunnels is mechanized excavation using an earth pressure balance (EPB) boring machine. Predicting the penetration rate of the boring machine can significantly reduce costs in mechanized excavation. Geological and geotechnical factors, machine specifications, and operational parameters can be influential on the penetration rate of the machine. Important geotechnical factors include cohesion, friction angle, and soil shear modulus. Among the important machine parameters, the thrust force of the jacks, the torque, and the rotational speed of the cutter head can be mentioned. In this study, after analyzing the main component, eliminating the outlier data, and normalizing the data, by considering the geotechnical factors and various parameters of the mechanized boring machine, the penetration rate of the EPB machine in the Tabriz metro line 2 tunnel has been predicted. For this purpose, linear regression methods, fuzzy logic using Mamdani and Sugeno algorithms, neuro-fuzzy method, and metaheuristic algorithms were used. To validate each model, statistical indices of the coefficient of determination (), root mean squares error (RMSE), and performance indicator (VAF) were used. The results of the studies showed that the neuro-fuzzy method has a better prediction of the penetration rate in comparison to other methods. Also, the results of the sensitivity analysis revealed that the cutter head torque had the greatest effect on the penetration rate of the EPB machine.

In this paper, we present an integrated model to find the optimum size of blast block that uses (i) a multi-criteria decision-making method to specify the applicable size of the mineable block; (ii) a linear programming method for the selection of the blasted areas to be excavated and in deciding the quantity of ores and wastes to be mined from each one of the selected blocks. These two methods use improved estimates of the orebody characteristics utilizing the blast hole data in addition to the usual borehole statistics to improve the prediction accuracy of the block level ore body characteristics. This work aims to make a mathematical model to figure out the ideal width and length of the blast block in order to curtail drilling and blasting expenses in open-pit mines. As a consequence, the effective blast block size is heeded so as to decrease the expenses of drilling and blasting. Furthermore, a complete set of actual principles is presented to specify the applicable size of the mineable block by means of the multi-criteria decision-making method of fuzzy logic. The aforementioned model is practiced to forecast the block size necessary for the purpose of production planning. Next, a mixed integer programming model is developed to blast planning in order to select the optimal size of the blast block by considering the mineable block. The proposed model is applied in the Chadormalu iron ore mine and the rationality of the model is demonstrated by the outcomes of dissimilar circumstances.