Failure Rate Prediction and Accelerated Detection of Anomalous Charge Loss in Flash Memories by Using an Analytical Transient Physics-Based Charge Loss Model

2002 ◽  
Vol 41 (Part 1, No. 4B) ◽  
pp. 2650-2653 ◽  
Author(s):  
Franz Schuler ◽  
Georg Tempel ◽  
Hanno Melzner ◽  
Michael Jacob ◽  
Paul Hendrickx ◽  
...  
1977 ◽  
Vol R-26 (3) ◽  
pp. 214-219 ◽  
Author(s):  
W.W. Gaertner ◽  
D.S. Elders ◽  
D.B. Ellingham ◽  
J.A. Kastning ◽  
W.M. Schreyer

2018 ◽  
Vol 44 ◽  
pp. 00086
Author(s):  
Małgorzata Kutyłowska

The paper presents the results of failure rate prediction using adaptive algorithm MARSplines. This method could be defined as segmental and multiple linear regression. The range of segments defines the range of applicability of that methodology. On the basis of operational data received from Water Utility two separate models were created for distribution pipes and house connections. The calculations were carried out in the programme Statistica 13.1. Maximal number of basis function was equalled to 30; so-called pruning was used. Interaction level equalled to 1, the penalty for adding basis function amounted to 2, and the threshold – 0.0005. GCV error equalled to 0.0018 and 0.0253 as well as 0.0738 and 0.1058 for distribution pipes and house connections in learning and prognosis process, respectively. The prediction results in validation step were not satisfactory in relation to distribution pipes, because constant value of failure rate was observed. Concerning house connections, the forecasting was slightly better, but still the overestimation seems to be unacceptable from engineering point of view.


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