Prediction of Soil Erosion Depth Due to Increase in Forest fire Danger Rate by Data Mining
Vijayalakshmi M. N · 2011
areas and unfarmed land fires have been witnessed in the history for loss of soil nutrient. Forest Fires is one of the sources of trouble for a long time. Fires for larger hectare have huge pressure over the ecological system (2) .It is required to calculate the fire danger rate, loss of land area due to forest fire, which further helps forest management in identification for loss of wild life in particular area. General Unary Hypotheses Automaton (GUHA) is used to predict the forest land area burnt in hectare (4).The fire danger rate is identified from the obtained result. Rules are generated on meteorological conditions. The patterns are recognized using temperature, rainfall and wind speed. This paper intends to identify the item set for loss of soil depth due to forest fire. Apriori algorithm is used to obtain frequent item sets. The item set are classified into rules for result. KeywordsUnary Hypotheses Automaton, Apriori algorithm, Forest fire, patterns.