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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