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2018 | 113 | 235-246
Article title

Computational Analysis of Screening Unit of Paper Plant with Human Error Using Neural Network Approach

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Abstracts
EN
Recent approach of Neural Network can be applied to solve a wide range of optimization problems. This paper deals with reliability, non-reliability and profit analysis of a paper plant. The objective of this paper is to compute profit of paper plant using neural network Algorithm and to analyze the availability of the system. The system is divided into four main subsystems. A multi-layered neural network model is used in order to optimize the maintenance of the paper plant system. The system may fail due to hardware failure with human errors and various environmental conditions. All types of failures, repairs and waiting rates are exponential. System state probabilities and other parameters are developed for the proposed model using neural network approach. Numerical examples are included to demonstrate the results.
Year
Volume
113
Pages
235-246
Physical description
Contributors
author
  • Department of Mathematics, KIET Group of Institutions, Ghaziabad, India
author
  • Department of Mathematics, KIET Group of Institutions, Ghaziabad, India
author
  • Department of Mathematics, KIET Group of Institutions, Ghaziabad, India
author
  • Department of Mathematics, KIET Group of Institutions, Ghaziabad, India
References
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  • [14] Watanade Chihiro, Hiramatsu Kaoru, Kashino Kunio, Modular Representation of layered neural networks, Neural Networks Journal 97, 2018, pp. 62-73
Document Type
article
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YADDA identifier
bwmeta1.element.psjd-a72d4e29-8180-47eb-b9ca-2f91bb493837
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