A Hybrid Intelligent System Integrating the Cascade Forward Neural Network with Elman Neural Network-Reference-Cited by-同舟云学术

A Hybrid Intelligent System Integrating the Cascade Forward Neural Network with Elman Neural Network

Published:2017-09-21 Issue:12 Volume:43 Page:6737-6749
ISSN:2193-567X
Container-title:Arabian Journal for Science and Engineering
language:en
Short-container-title:Arab J Sci Eng

Author:

Alkhasawneh Mutasem Sh.,Tay Lea Tien

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://link.springer.com/article/10.1007/s13369-017-2833-3/fulltext.html

Reference36 articles.

1. McCulloch, W.W.P.: Logical calculus of ideas immanent in nervous activity. Bull. Math. Biophys. 5(4), 115–133 (1943)

2. Kit-Po, W.: Artificial intelligence and neural network applications in power systems. In: 2nd International Conference on Advances in Power System Control, Operation and Management, 1993. APSCOM-93 (1993)

3. Classification, D.U.F.: Comparison of results. Nicolaus Copernicus University, Department of Informatics (2008). http://www.fizyka.umk.pl/kmk/projects/datasets.html

4. Hoang, A.: Supervised classifier performance on the UCI database. Master Thesis, Department of Computer Science, University of Adelaide, Adelaide (1997)

5. Eklund, P.; Hoang, A.: A comparative study of public domain supervised classifier performance on the UCI database. Research Online (2006-01-01)

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