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Intelligent Engineering Systems through Artificial Neural Networks
ISBN:
9780791802953
No. of Pages:
636
Publisher:
ASME Press
Publication date:
2009
eBook Chapter
20 Ann-Based Profiling: Data Importance
By
Yacoub Najjar
,
Yacoub Najjar
Kansas State University
2118 Fiedler Hall Civil Engineering Department Manhattan, KS 66506
USA
; ea4146@ksu.edu
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Sam Mryyan, PhD, REM
Sam Mryyan, PhD, REM
Environmental Compliance Manager Adjutant General's Department 2800 SW Topeka Blvd.
Topeka, KS 66611
USA
; sam.mryyan@us.army.mil
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Page Count:
8
-
Published:2009
Citation
Najjar, Y, & Mryyan, S. "Ann-Based Profiling: Data Importance." Intelligent Engineering Systems through Artificial Neural Networks. Ed. Dagli, CH, Bryden, KM, Corns, SM, Gen, M, Tumer, K, & Süer, G. ASME Press, 2009.
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ANN with a back-propagation learning algorithm was developed to model the data importance at the Massachusetts Military Reservation site. In various testing trials, thirty-three back-propagation ANN models were developed, which excluded or included certain groundwater monitoring wells. These models were then used to investigate the minimum number of groundwater wells necessary to characterize the Demo 1 site accurately.
Topics:
Artificial neural networks
Abstract
1.0 Introduction
2.0 Background of Study Area
3.0 ANN Model Development
4.0 Contour Maps
5.0 Results and Discussion
6.0 Discussion
7.0 Conclusion
References
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