Earticle

초록

영어

In order to precisely predict the location of forest fire, a new algorithm based on improvement of gravity center scan method is introduced in this paper. The new algorithm suppressed error rate of InToOut and OutToIn. By using the neighbor nodes around the unknown nodes, it solved the problem of less signal flag nodes around unknown nodes, furthermore, it improved the coverage of nodes and suppressed error rate the location of node. The simulation result shows that, along with the increment of the density of signal flag nodes, the error rate of location of unknown nodes is gradually decreasing. In networks with limited signal flag nodes, the new algorithm based on improved gravity scan suppressed the error rate by 40%, compared with previous gravity scanning algorithm, which dramatically improved the precision of location.

목차

Abstract
 1. Introduction
  1.1. APIT Algorithm Defects
  1.2. Performance Comparison of Improved APIT Algorithm
  1.3. APIT Test Theory Correction
  1.4. Achievement in the Gravity Scanning Algorithm
 2. Improved theory of Gravity Scanning Localization Algorithm
  2.1. In Figure 1., there are 3 Beacon Nodes Around Unknown Node
  2.2. In Figure 2., there are 4 Beacon Nodes Around Unknown Node
  2.3. In Figure 3., there are 5 Beacon Nodes Around Unknown Node
 3. The Basic Idea of improved Gravity Scanning Algorithm
 4. Realization of the improved Gravity Scanning Localization Algorithm
 5. The Simulation Realization of the improved Gravity Scanning Algorithm
  5.1. Comparison of Positioning Error Rate
  5.2. Comparison of Positioning Error and Coverage Rate
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Dan Liu [ Northeast Forestry University ]
• Yanrong Zhang [ Harbin University of Commerce ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605