study on a fire detection system based on support vector machine

study on a fire detection system based on support vector machine

;Ye Xiaoting;Wu Shasha;Xu Jingjing
gülhane tıp dergi 2014 Vol. 182 pp. 57-61
157
xiaoting2014sensorsstudy

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.

Citation

ID: 142308
Ref Key: xiaoting2014sensorsstudy
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
142308
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet