Earticle

초록

영어

Localization is one of the most important research topics in the wireless sensor network applications. To improve the indoor localization accuracy, the centroid localization algorithm based on Mamdani fuzzy system has been adopted to attain the weight between sensor node and anchor node. This paper proposes a novel optimized input membership function by bat algorithm in fuzzy inference system using the data of received signal strength in real indoor condition. The author has realized the algorithm on Zigbee platform and the experimental comparison on other different centroid localization algorithms indicates that Mamdani fuzzy inference adopting the membership function optimized by bat algorithm renders smaller mean localization errors.

목차

Abstract
 1. Introduction
 2. Localization Algorithm Model
  2.1. RSS Features and Ranging Model Analysis
  2.2. Weighted Centroid Localization Algorithm
  2.3. Bat Algorithm
 3. Fuzzy Inference System
  3.1. Input Membership Function
  3.2. Output Membership Function
  3.3. Fuzzy Rules
  3.4 Fuzzy Inference Process
 4. Experiment and Analysis
  4.1. Experimental Environment Setting
  4.2. Hardware of Localization System
  4.3. Average Localization Error
  4.4. Experiment and Analysis
 5. Conclusions
 References

키워드

저자

• Hao Shi [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]
• Wanliang Wang [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]
• Liangjin Lu [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605