Abstract
In this study, the application of Artificial Neural Network (ANN) for home security system (HSS) is investigated. The HSS consists of a neural network with input, hidden and output layers. The HSS detects the presence of unidentified person in the house and initiates an alarm. It has its own fault-diagnostic algorithm. In case any system component fails, it gives an alarm which is different from the other, to indicate the system failure. The minimum number of nodes, the optimum number of hidden layers, the speed, the accuracy and learning time for back propagation (BP) algorithm [1] are investigated in the present paper.
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References
D.E. Rumelthart, Hinton, and R. Willaiams: Parallel Distributed Processing Vol I. Chap. 8. (1990)
David L. Bailey and Donna Thompson: Developing Neural Network Applications AI Expert 34 (1990)
David L. Bailey and Donna Thompson: How to Develop Neural Network, AI Expert, June 1990, pp 36–47.
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© 1995 Springer-Verlag/Wien
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Ibrikci, T., Krishnamurthi, V. (1995). Application of Neural Network for Home Security System. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_116
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_116
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
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