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A Pattern Adaptive Technique to Handle Data Quality Variation (1999)

Wong, P. M. ; Gedeon, T. D.

Springer

Neural processing letters 10 (1999), S. 7-15

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ISSN: 1573-773X

Keywords: well logging ; outliers ; permeability

Source: Springer Online Journal Archives 1860-2000

Topics: Computer Science

Notes: Abstract This study proposes a new technique, namely the Pattern Adaptive Neural Network (PANN), for simplifying existing noise detection and removal methods. This technique is developed based on a modified backpropagation algorithm using a fuzzy membership function on the error term. It is able to make use of noisy data in a single step, with an automatic adjustment of data contribution to network training. It is demonstrated via an application on an oil well data set. The results show that the predictions from PANN matched well with the expert interpretations on the data set regarding the data quality.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1023/A:1018602627915

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