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A Neural Network Approach to Fluid Quantity Measurement in Dynamic EnvironmentsDiscussion

A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments: Discussion [This chapter discusses the design and optimal selection of parameters of the ANN-based signal processing system. The selection of optimal preprocessing parameters used in the ANN-based measurement system and the results obtained from the experimentations, and the possible improvements to design of the ANN based system, are all discussed in this section.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

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Publisher
Springer London
Copyright
© Springer-Verlag London 2012
ISBN
978-1-4471-4059-7
Pages
121 –127
DOI
10.1007/978-1-4471-4060-3_7
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter discusses the design and optimal selection of parameters of the ANN-based signal processing system. The selection of optimal preprocessing parameters used in the ANN-based measurement system and the results obtained from the experimentations, and the possible improvements to design of the ANN based system, are all discussed in this section.]

Published: Apr 21, 2012

Keywords: Preprocessing Parameters; Feature Extraction Function; Signal Smoothing; Statistical Averaging Methods; Network Classification Accuracy

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