ARTIFICIAL NEURAL NETWORK APPLICATION FOR ERROR ESTIMATION IN WIRELESS SENSOR NETWORK

Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/15254

Title:	ARTIFICIAL NEURAL NETWORK APPLICATION FOR ERROR ESTIMATION IN WIRELESS SENSOR NETWORK
Authors:	James, Aagajo Jonathan, Gana Kolo Danlami, Maliki Umar, Buhari Ugbede Ogbole, Inalegwu Collins
Keywords:	Packet, Data, Neural Network, Wireless Sensor Nerwork
Issue Date:	1-Jun-2017
Publisher:	Proceedings of ISER 57th International Conference, Dubai, UAE, 1st -2nd June 2017
Abstract:	This paper comes up with an error estimation model for Wireless Sensor Nodes,, the integrity of data received after transmission within a signal coverage range less or equal to 45 meters is analysed, Neural Network linear regression method was used to evolve resolve equation that compares error with weight of data received as δ℮(w) against δwij , an equation for error rate was also evolved after carefully comparing between data packet transmitted and Packet received, error rate er for sensor node was calculated to be 0.00918 thereby establishing the fact that expected packet to be received for every data transmitted is the product of er and Packet Transmitted.
URI:	http://repository.futminna.edu.ng:8080/jspui/handle/123456789/15254
Appears in Collections:	Computer Engineering

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