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Intelligent Engineering Systems through Artificial Neural Networks
Editor
Cihan H. Dagli
Cihan H. Dagli
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K. Mark Bryden
K. Mark Bryden
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Steven M. Corns
Steven M. Corns
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Mitsuo Gen
Mitsuo Gen
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Kagan Tumer
Kagan Tumer
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Gürsel Süer
Gürsel Süer
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ISBN:
9780791802953
No. of Pages:
636
Publisher:
ASME Press
Publication date:
2009

In this paper, we study a real multi-classification problem. The goal is to predict the weathering degrees of drilling core samples in situ, on the basis of their color. These weathering degrees (6 classes) are provided by an expert (geologist) and validated by chemical analysis. Our objective is to build a classifier making possible the prediction of the weathering degrees according to the color parameters measured with a spectrophotometer. After choosing the colorimetric system, we propose a features selection method. Then, we build two classifiers: one based on a perceptron multi-layer neural network (NN) and the other based on the fuzzy k-nearest-neighbor (knn) methods. Comparison of results between the methods used and other classical ones are given.

Abstract
Introduction
Samples and Color Parameters Acquisition
NN and Fuzzy Classification Methods
Conclusions and Future Work
References
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