DocumentCode :
567845
Title :
A development of snake bite identification system (N´viteR) using Neuro-GA
Author :
Halim, Shamimi A. ; Ahmad, Azlin ; Noh, Norzaidah Md ; Ali, Azliza Mohd ; Abdul Hamid, Nurzeatul Hamimah ; Yusof, Siti Farah Diana ; Osman, Rozianawaty ; Ahmad, Rashidi
Author_Institution :
Fac. of Comput. & Math. Sci., Univ. Teknol. MARA, Shah Alam, Malaysia
Volume :
1
fYear :
2012
fDate :
3-5 Aug. 2012
Firstpage :
490
Lastpage :
494
Abstract :
It is crucial to differentiate between venomous and non-venomous snake whereby an immediate and effective medical care can be instituted to the victims. However, early identification is not easy. We developed a snake bite identification system (N´viteR) to differentiate the snake using Neuro-GA technique. Based on 200 cases, this work had revealed that Neuro-GA has yield a high accuracy in identifying the snake. A number of experiments have been done which based on number of epoch, momentum, learning rate, number of generation, population and chromosome. This hybrid technique has achieved 97.6% of accuracy which enables early identification of snake and immediate specific anti-venom can be administered. Hence, reduces the rate of morbidity and mortality.
Keywords :
genetic algorithms; health care; neural nets; N´viteR; hybrid technique; medical care; neuro-GA technique; non-venomous snake; snake bite identification system; specific anti-venom; venomous snake; Biological cells; Educational institutions; Hemorrhaging; Learning systems; Back Propagation Neural Network; Genetic Algorithm; Neuro-GA; identification accuracy; snake identification; snake identification system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology in Medicine and Education (ITME), 2012 International Symposium on
Conference_Location :
Hokodate, Hokkaido
Print_ISBN :
978-1-4673-2109-9
Type :
conf
DOI :
10.1109/ITiME.2012.6291349
Filename :
6291349
Link To Document :
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