A Ranging Model Based on BP Neural Network. Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Chen, Xiaohui; Zhang, Mengjiao; Ruan, Kai; Gong, Canfeng; Zhang, Yinyin; Yang, Simon X.
• Is Part Of: Intelligent automation & soft computing. Volume 22:Issue 2(2016)
• Page Start: 325
• Page End: 329
• Publication Date: 2016-04-02
• Subjects: Shadowing model -- BP neural network model -- WSN -- Ranging error -- Adaptability; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2015.1095484
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: The traditional Shadowing model relies too much on parameters and specific environment, so its application occasions in WSN are restricted. This paper studies the wireless signal propagation model and proposes the ranging model based on BP neural network model, it has the ability of autonomous learning according to different environments, and can improve the precision of measuring distance, then enhance the adaptability to the environment. The simulation results show that the ranging model based on BP neural network model can reduce the ranging error, which has the adaptability to the environment.