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A proposed life cycle forecasting model of complex recycling technical systems by implementing neural super network

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2 Author(s)
Khalil A. Yaghi ; Department of Management Information Systems, Applied Science Private University, Jordan ; Waheeb A. Abu-Dawwas

The purpose of this paper is to increase the efficiency of functionality and reliability of complex recycling technical systems (CRTS) community, through improving the control quality of their life cycle. Automated control system (ACS) on the basis of neural super-network learning for forecasting damages and ensuring its information representation for learning was proposed. In the paper it was suggested an architecture and a method of learning of a neural super-network for forecasting the progress of CRTS community life cycle.

Published in:

2009 First International Conference on Networked Digital Technologies

Date of Conference:

28-31 July 2009