Title: Prediction parameters in nano fibre composite membrane for effective air filtration using optimal neural network

Authors: Veeracholapuram Subburathinam Kandavel; Gabriel Mohan Kumar

Addresses: Mechanical Department, Kalaignar Karunanidhi Institute of Technology, Coimbatore, India ' Department of Mechanical Engineering, PARK College of Engineering and Technology, Coimbatore, India

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.

Keywords: nanonets; composite membrane; high efficiency; neural network and optimisation techniques.

DOI: 10.1504/IJBIDM.2018.094979

International Journal of Business Intelligence and Data Mining, 2018 Vol.13 No.4, pp.388 - 405

Accepted: 07 Jan 2017
Published online: 17 Jan 2018 *

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