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Wild Conservation Burnt Area Prediction by Data Mining
| 2nd National Conference on Information and Communication Technology |
| Foundation of Computer Science USA |
| NCICT - Number 5 |
| November 2011 |
| Authors: Divya T.L, Dr. Vijayalakshmi M.N |
| 4ea5c8b2-3035-40b5-b927-8b7910d086c0 |
Divya T.L, Dr. Vijayalakshmi M.N . Wild Conservation Burnt Area Prediction by Data Mining. 2nd National Conference on Information and Communication Technology. NCICT, 5 (November 2011), 9-11.
Abstract
Forest fire is major risk in mediterranean forest area. During summer high temperature and low humidity will cause this problem in wild conservation space. Forest and uncultivated land fires have been witnessed in the past for loss of soil nutrient. Forest Fires is a source of trouble for a long time. Fires for larger hectare have considerable pressure over the ecological system [2] .It is required to calculate the loss of land area due to forest fire, which further helps forest management in identification of soil erosion and loss of wild life in particular area. General Unary Hypotheses Automaton (GUHA) is used to predict the forest land area burnt in hectare. Rules are generated on meteorological conditions. The patterns are recognized using temperature, rainfall and wind speed. This paper intends to identify the item set of weather relation with the size of forest land area in hectare. We have used only three meteorological set of data to predict the loss of land area. The item set are classified into rules for decision making.
References
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