study on a fire detection system based on support vector machine

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ID: 142308
2014
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Abstract
It is very important to research the prediction of fire, which is significant to the people and nation. The traditional fire detection system based on neural network has the disadvantages of over learning, trapped in local minimum, etc. This paper proposes a new fire detection system based on support vector machine (SVM). Gas sensors, smoke sensor and temperature sensor are composed to be a sensor array. The fire detection model is established, including sample selection, prediction model training prediction, output modules, etc. The SVM transform the complicated nonlinear problem into the linear problem in the high dimensional plane. The experimental results show that fire detection system based on support vector machine had high recognition rate and reliability, it overcomes the disadvantages of traditional methods.
Reference Key
xiaoting2014sensorsstudy Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Ye Xiaoting;Wu Shasha;Xu Jingjing
Journal gülhane tıp dergi
Year 2014
DOI
DOI not found
URL
http://www.sensorsportal.com/HTML/DIGEST/november_2014/Vol_182/P_2500.pdf
Keywords
support vector machine Technology (General) pattern recognition

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