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Adaptive Network Structures for Data/Text Pattern Recognition (Application)

Adaptive Network Structures for Data/Text Pattern Recognition (Application)

Emmanuel Buabin
Copyright: © 2013 |Pages: 15
ISBN13: 9781466626614|ISBN10: 1466626615|EISBN13: 9781466626928
DOI: 10.4018/978-1-4666-2661-4.ch023
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MLA

Buabin, Emmanuel. "Adaptive Network Structures for Data/Text Pattern Recognition (Application)." Graph Theory for Operations Research and Management: Applications in Industrial Engineering, edited by Reza Zanjirani Farahani and Elnaz Miandoabchi, IGI Global, 2013, pp. 280-294. https://doi.org/10.4018/978-1-4666-2661-4.ch023

APA

Buabin, E. (2013). Adaptive Network Structures for Data/Text Pattern Recognition (Application). In R. Farahani & E. Miandoabchi (Eds.), Graph Theory for Operations Research and Management: Applications in Industrial Engineering (pp. 280-294). IGI Global. https://doi.org/10.4018/978-1-4666-2661-4.ch023

Chicago

Buabin, Emmanuel. "Adaptive Network Structures for Data/Text Pattern Recognition (Application)." In Graph Theory for Operations Research and Management: Applications in Industrial Engineering, edited by Reza Zanjirani Farahani and Elnaz Miandoabchi, 280-294. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2661-4.ch023

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Abstract

The objective of this chapter is implementation of neural based solutions in real world context. In particular, a step-wise approach to constructing, training, validating, and testing of selected feed-forward (Multi-Layer Perceptron, Radial Basis function) and recurrent (Recurrent Neural Networks) neural based classification systems are demonstrated. The pre-processing techniques adopted in extracting information from selected datasets are also discussed. In terms of future practical directions, a catalogue of intelligent systems across selected disciplines, are outlined. The main contribution of this book chapter is to provide basic introductory text with less mathematical rigor for the benefit of students, tutors, lecturers, researchers, and/or professionals who wish to delve into foundational (practical) representations of bio-intelligent intelligent systems.

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