Leave-One-Out Cross-Validation Analysis
In this section Leave-One-Out Cross-Validation (LOOCV) was followed with the aim of training and testing the ANN model. In this way, frequently, one sample is kept for testing while the rest is used for training up to all samples are finally tested (26). Before the proposed model is applied to the particular application it must be trained using all available samples (27). The difference between the observed and the predicted values are shown in Fig. 11. The training of network continued until maximum correlation within the measured and predicted output was achieved (Table 3). Correlation expressed by R squared that R2 is coefficient of multiple determinations and relative root mean square error (RMSE) (26). Correlation results are perfect when an R squared value of 1, a very good fit is next to 1 and a very poor fit less than 0. On the other side, how much the value of RRMSE is smaller; the performance of the model is better.
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12, the annually averaged results of passive sampling are presented. Exposure values in terminals were generally higher than other are.
As it can be seen there is seasonal variation especially in outdoor units. Ambient air temperature affects significantly the exposure levels as a result the high temperatures in the summer and spring explain the increased benzene concentrations in exposure values. When temperatures are very low (wintertime), the exposure levels are less than usual for an equivalent quantity of close benzene level (Fig. 13).
It appears that the presence of wind reduce exposure levels, especially to employees who are performing outdoor activities. No strong correlation found between wind speed and exposure levels of employees working in laboratory and control room.
Health risk assessment
12, the annually averaged results of passive sampling are presented. Exposure values in terminals were generally higher than other are.
As it can be seen there is seasonal variation especially in outdoor units. Ambient air temperature affects significantly the exposure levels as a result the high temperatures in the summer and spring explain the increased benzene concentrations in exposure values. When temperatures are very low (wintertime), the exposure levels are less than usual for an equivalent quantity of close benzene level (Fig. 13).
It appears that the presence of wind reduce exposure levels, especially to employees who are performing outdoor activities. No strong correlation found between wind speed and exposure levels of employees working in laboratory and control room.
Health risk assessment