The Effects of ZigBee Position with Different Hidden Layers in Back-Propagation Neural Network

Abstract:

In this paper, the research topic is that the expert experience is established by the size of the measured signal strength of wireless sensor networks and put the strength of the actual collection of historical data into the neural network model. In order to get the minimize error we use the errors to modify the weights and threshold of the neural network links. We compare the differences of hidden layer neural network and the experimental results. We set up a wireless sensor networks environment to collect the measurement values of signal strength (RSSI) and develop an indoor positioning system.

• Periodical: Advanced Materials Research (Volumes 189-193)
• Pages: 1761-1767
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.189-193.1761
• Online since: February 2011
• Authors: Fang Tsung Liu, Ceweng Erh Weng, Chien Ming Huang, Chang Yan Yang, Huang Chu Huang
• Keywords: Neural Network (NN), Positioning System, Signal Strength

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