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| Content Provider | Springer Nature Link |
|---|---|
| Author | Dutta, Debashree Chaudhuri, Sutapa |
| Copyright Year | 2014 |
| Abstract | The endeavor of the present research is to nowcast the spatial visibility during fog over the airport of Kolkata (22.6°N; 88.4°E), India, with artificial neural network (ANN) model. The identification of dominant parameters influencing the visibility during wintertime (November–February) fog over the region is made using the decision tree algorithm. The decision tree is constructed by computing the entropy of the parameters collected during the period from 2001 to 2011. The parameters having minimum entropy are selected as the most useful parameters because it has maximum certainty in influencing the visibility. The result reveals that the moderate range of NO$_{2}$ (67–134 µg/m$^{3}$) is the most dominant parameter compared with other parameters that influence the visibility during wintertime fog over Kolkata and is selected as the first node of the tree. The decision tree approach led to select five such parameters having minimum entropy for affecting maximum the visibility during fog over Kolkata airport. The selected parameters are NO$_{2}$, wind speed, relative humidity, CO and temperature. ANN model is developed with the selected parameters as the input in the form of multilayer perceptron with back propagation learning technique for forecasting the 3 hourly visibility during wintertime fog over Kolkata airport. The result reveals that the forecast of visibility of different categories is possible with ANN model. However, the best forecast is obtained for very dense visibility within the 50 m horizontal distance. The result is validated with observation, and the forecast error is estimated. |
| Starting Page | 1349 |
| Ending Page | 1368 |
| Page Count | 20 |
| File Format | |
| ISSN | 0921030X |
| Journal | Natural Hazards |
| Volume Number | 75 |
| Issue Number | 2 |
| e-ISSN | 15730840 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2014-09-04 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Decision tree algorithm Artificial neural network model Multilayer perceptron Forecast skill Entropy NO$_{2}$ Wind speed Relative humidity CO and temperature Natural Hazards Hydrogeology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Civil Engineering Environmental Management |
| Content Type | Text |
| Resource Type | Article |
| Subject | Atmospheric Science Water Science and Technology |
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