Adaptive Neuro-Fuzzy Inference System for Prediction of Effective Thermal Conductivity of Polymer-Matrix Composites

ISSN Print: 2164-5345
ISSN Online: 2164-5353
www.scirp.net/journal/mnsms
E-mail: [email protected]

Citations

"Adaptive Neuro-Fuzzy Inference System for Prediction of Effective Thermal Conductivity of Polymer-Matrix Composites"
written by Rajpal Singh Bhoopal, Ramvir Singh, Pradeep Kumar Sharma,
published by Modeling and Numerical Simulation of Material Science, Vol.2 No.3, 2012

has been cited by the following article(s):

[1]	Emerging Technologies for Resilient Infrastructure: Conspectus and Roadmap
	2021

[2]	Hazard-Resilient Infrastructure: Analysis and Design
	2021

[3]	Determination of dielectric properties of natural fiber reinforced polymer composite using adaptive neuro fuzzy inference system
	Materialwissenschaft …, 2021

[4]	Neuro-fuzzy based approach for prediction of blast-induced ground vibration
	2019

[5]	Neuro-fuzzy based approach for estimation of concrete compressive strength
	2018

[6]	Evaluation of Ground Vibration Due to Blasting Using Fuzzy Logic
	Geotechnical and Geological Engineering, 2017

[7]	Interfacial Layer Effect on the Thermal Conductivity of Nano-Fluids
	Advanced Science, Engineering and Medicine, 2016

[8]	Hybrid of neuro-fuzzy inference system and quantum genetic algorithm for prediction in stock market
	Issues in Business Management and Economics (IBME), 2014

[9]	Effective Thermal Conductivity of Polymer Composites Using Local Fractal Techniques
	International Journal of Innovative Technology and Exploring Engineering, 2013

[10]	APPLICABILITY OF ARTIFICIAL NEURAL NETWORKS TO PREDICT EFFECTIVE THERMAL CONDUCTIVITY OF HIGHLY POROUS METAL FOAMS
	Journal of Porous Media, 2013

[1]	An analysis of single conductive filler-reinforced HDPE composites: a material-centric pathway toward metal-based conductivity enhancement Polymer Bulletin, 2026 DOI:10.1007/s00289-026-06421-6

[2]	Evaluation of Ground Vibration Due to Blasting Using Fuzzy Logic Geotechnical and Geological Engineering, 2017 DOI:10.1007/s10706-017-0162-7