Disaster Impact Mitigation using KDD and Support Vector Machine algorithms
Journal Title: EAI Endorsed Transactions on Energy Web - Year 2018, Vol 5, Issue 18
Abstract
Disasters such as Hurricanes, Typhoons, Floods and earthquakesare not good for the society since it causes serious damage for the society. A natural disaster causes loss in property as well as in life of victims. The victims need immediate help once they are affected by the disaster. The immediate need are rescue, food and communications. The survey says victims of recent disaster were unable to get instant communication regarding the evacuation path and other help from authorities for remedial action. This can be overcome with our proposed idea of having a database of area wise population along with the pre-disaster and post-disaster satellite images of the disaster affected area. Knowledge Discovery in Databases (KDD) is used in data pre-processing and to extract knowledge from the database. Support vector machine(SVM) is used to classify the disaster effect with the pre-disaster and post-disaster satellite images as input. The idea is implemented and tested with sample data and has given impressive results
Authors and Affiliations
D. John Aravindhar, M. N. Sushmitha, K. Padmaveni
Keywords
Related Articles
- EP ID EP45362
- DOI http://dx.doi.org/10.4108/eai.12-6-2018.154812
- Views 265
- Downloads 0
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