Prediction parameters in nano fibre composite membrane for effective air filtration using optimal neural network
by Veeracholapuram Subburathinam Kandavel; Gabriel Mohan Kumar
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 13, No. 4, 2018

Abstract: The capacity to build up steady and extensive trench structures by means of headed for great degree thin fibres would have wide innovative ramifications. Here, we report a procedure to plan and make sandwich organised polyamide-6/polyacrylonitrile/polyamide-6 (PA-6/PAN/PA-6) composite membrane is considered. This is sensible for powerful air filtration via consecutive electro spinning by coordinating the elements of parts to foresee the distinctive mechanical properties with help of optimal weight of ANN structure. Distinctive inspired optimisation strategies are used to touch base at the optimal weight of the ANN procedure. All the ideal results exhibit the way that the accomplished error values between the yield of the exploratory qualities and the anticipated qualities are firmly equivalent to zero in the outlined network. In addition, the most intense filtration accuracy and lower pressure drops furthermore the result demonstrates the base error of 96.72% dictated by the ANN. This is accomplished by the artificial fish swam optimisation (AFSO) strategies.

Online publication date: Fri, 28-Sep-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com