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Artificial Neural Network What-If Theory

Artificial Neural Network What-If Theory

Paolo Massimo Buscema, William J. Tastle
Copyright: © 2015 |Volume: 6 |Issue: 4 |Pages: 30
ISSN: 1941-868X|EISSN: 1941-8698|EISBN13: 9781466676923|DOI: 10.4018/IJISSC.2015100104
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MLA

Buscema, Paolo Massimo, and William J. Tastle. "Artificial Neural Network What-If Theory." IJISSC vol.6, no.4 2015: pp.52-81. http://doi.org/10.4018/IJISSC.2015100104

APA

Buscema, P. M. & Tastle, W. J. (2015). Artificial Neural Network What-If Theory. International Journal of Information Systems and Social Change (IJISSC), 6(4), 52-81. http://doi.org/10.4018/IJISSC.2015100104

Chicago

Buscema, Paolo Massimo, and William J. Tastle. "Artificial Neural Network What-If Theory," International Journal of Information Systems and Social Change (IJISSC) 6, no.4: 52-81. http://doi.org/10.4018/IJISSC.2015100104

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Abstract

Data sets collected independently using the same variables can be compared using a new artificial neural network called Artificial neural network What If Theory, AWIT. Given a data set that is deemed the standard reference for some object, i.e. a flower, industry, disease, or galaxy, other data sets can be compared against it to identify its proximity to the standard. Thus, data that might not lend itself well to traditional methods of analysis could identify new perspectives or views of the data and thus, potentially new perceptions of novel and innovative solutions. This method comes out of the field of artificial intelligence, particularly artificial neural networks, and utilizes both machine learning and pattern recognition to display an innovative analysis.

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