On the Power Efficiency of Artificial Neural Network (ANN) and the Classical Regression Model
This research work presents new development in the field of natural science, where comparison is made theoretically on the efficiency of both classical regression models and that of artificial neural network models, with various transfer functions without data consideration. The results obtained based on variance estimation indicates that ANN is better which coincides with the results of Authors in the past on the efficiency of ANN over the traditional regression models. The certain conditions required for ANN efficiency over the conventional regression models were noted only that the optimal number of hidden layers and neurons needed to achieve minimum error is still open to further investigation.
- There are currently no refbacks.
If you have already registered in Journal A and plan to submit article(s) to Journal B, please click the CATEGORIES, or JOURNALS A-Z on the right side of the "HOME".
We only use the follwoing mailboxes to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
Copyright © 2010 Canadian Research & Development Center of Sciences and Cultures
Address: 730, 77e AV, Laval, Quebec, Canada H7V 4A8
Telephone: 1-514-558 6138
E-mail:email@example.com firstname.lastname@example.org email@example.com