Artifificial Neural Network Application for Error Estimation in Wireless Sensor Network

Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8767

Title:	Artifificial Neural Network Application for Error Estimation in Wireless Sensor Network
Authors:	Agajo, James Kolo, J.G. Maliki, Danlami Umar, Buhari Collins, Ogbole I.
Keywords:	Packet Data Neural network Wireless sensor network
Issue Date:	Jun-2017
Citation:	James Agajo, Jonathan G. Kolo, Danlami Maliki, Buhari Umar, Ogbole I. Collins, "Artifificial Neural Network Application for Error Estimation in Wireless Sensor Network", Proceedings of ISER 57th International Conference, June 1-2, 2017, Dubai, UAE, Pp 22-26
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 metres is analysed, Neural Network linear regression method was used to evolve resolve equation that compares error with weight of data received as de(w) against dwij , 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 the product of er and Packet Transmitted.
URI:	http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8767
Appears in Collections:	Electrical/Electronic Engineering

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