Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Artificial Neural Network What-If Theory

Artificial Neural Network What-If Theory
View Sample PDF
Author(s): Paolo Massimo Buscema (Semeion Research Institute, Rome, Italy & University of Colorado, USA) and William J. Tastle (Ithaca College, USA)
Copyright: 2020
Pages: 29
Source title: Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-0414-7.ch001


View Artificial Neural Network What-If Theory on the publisher's website for pricing and purchasing information.


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.

Related Content

Paolo Massimo Buscema, William J. Tastle. © 2020. 29 pages.
Uthra Kunathur Thikshaja, Anand Paul. © 2020. 11 pages.
Arvind Kumar Tiwari. © 2020. 11 pages.
Srijan Das, Arpita Dutta, Saurav Sharma, Sangharatna Godboley. © 2020. 17 pages.
Mohammed E. El-Telbany, Samah Refat, Engy I. Nasr. © 2020. 13 pages.
Ashraf M. Abdelbar, Islam Elnabarawy, Donald C. Wunsch II, Khalid M. Salama. © 2020. 14 pages.
Saifullah Khalid. © 2020. 12 pages.
Body Bottom