European Academic Research ISSN 2286-4822
ISSN-L 2286-4822
Impact Factor: 3.4546 (UIF)
DRJI Value : 5.9 (B+)
Article Details :
Article Name :
Evaluation of Environmental Hazard in Underground Mines Using Adaptive Neuro- Fuzzy Model
Author Name :
Eman Sarwat
Publisher :
Bridge Center
Article URL :
Abstract :
Appropriate measurement of radon and thoron in mines should be maintained to avoid their high concentrations that have, been known to be a contributing cause for lung cancer. The measurements of radio nuclei are difficult in long mines as it takes more effort and time. For this concern, adaptive Neuro-Fuzzy inference system (ANFIS) is used in the reported study to estimate the concentration of radon (Rn) and thoron (Th) daughter (D) in two phosphate mines in Egypt. Comparison of the performance of experimental readings and ANFIS estimation is done. To obtain the best input-output mapping, two different models with various input combinations are evaluated for the two mines using ANFIS. In the first model, the ANFIS training process is applied using 50% of the reading data in consequent measurment for Rn and Th (D) with respect to the distance then predicting the rest of their concentrations. In the second model 50% of random measured data for Rn and Th (D) at different distances in the mine are taken and predicting the measurements in between. Standard performance indices, such as mean absolute error (MAE) and mean absolute percentage error (MAPR) are used to compare the performance of the two models. The second model which considers random data as input to the ANFIS produced the best results. Finally, the general measured results and their estimation will be used as bases to describe corrective actions based on underground mines radiological safety regulations.
Keywords :
Fuzzy Inference System, Mines, Radon and Thoron Estimation, Radiological Safety Regulation.

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