A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journal of Intelligent Learning Systems and Applications

ISSN Print: 2150-8402
ISSN Online: 2150-8410
www.scirp.org/journal/jilsa
E-mail: jilsa@scirp.org

Google-based Impact Factor: 1.5
Citations h5-index & Ranking*

Journals Menu

"A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour"
written by Xiaoguang Yang, Mohammad Behroozi, Oluremi A. Olatunbosun,
published by Journal of Intelligent Learning Systems and Applications, Vol.6 No.1, 2014

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Automatic Full Slip Detection System implemented on the Strain-based Intelligent Tire at severe maneuvers
	Petit, D García-Pozuelo, V Díaz… - … Systems and Signal …, 2023

[2]	Smart automobile health monitoring system
	Multimedia Technologies in the …, 2022

[3]	Tyre Design and Optimization by Dedicated CAD Tyre Model
	Tehnički vjesnik, 2021

[4]	Tire Deformation Modeling and Effect on Aerodynamic Performance of a P2 Race Car
	2021

[5]	The pneumatic wheel model with plastic elements and force loss
	2021

[6]	Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0
	2020

[7]	Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm
	2019

[8]	Exploring Neural Network to Predict Car Tyre Inflation Time and Power Requirement of a Tyre Pressure Control Unit.
	2019

[9]	Multi-chamber tire concept for low rolling-resistance
	2019

[10]	Hybrid Automaton Based Vehicle Platoon Modelling and Cooperation Behaviour Profile Prediction
	Tehni?ki vjesnik, 2018

[11]	Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network
	Polymers, 2018

[12]	Developments in tyre design for lower rolling resistance: a state of the art review
	Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2017

[13]	Neuro-fuzzy prediction of cooperation interaction profile of flexible road train based on hybrid automaton modeling
	2016

[14]	A procedure for multi-objective optimization of tire design parameters
	International Journal of Industrial Engineering Computations, 2015

[15]	FE-Based Tire Loading Estimation for Developing Strain-Based Intelligent Tire System
	2015

[16]	Speed Profile Prediction in Intelligent Transport Systems Exemplified by Vehicle to Vehicle Interactions
	Cybernetics and Information Technologies, 2015

[17]	Nonlinear finite element modeling and analysis of tire debris impact on aircraft structural components
	2015

[18]	Využití FEM pro návrh tvaru a konstrukce zemědělských pneumatik
	2015

[19]	FEM BASED PARAMETRIC DESIGN STUDY OF THE TIRE PROFILE USING DEDICATED CAD MODEL AND TRANSLATION CODE
	Facta Universitatis, Series: Mechanical Engineering, 2014

[20]	Development of Regression Models to Measure Energy and Inflation Time of a Fabricated Tyre Pressure Control Unit

[1]	Topological Optimization of Non-Pneumatic Unique Puncture-Proof Tire System Spoke Design for Tire Performance SAE International Journal of Passenger Vehicle Systems, 2023 DOI:10.4271/15-17-01-0001

[2]	Research Anthology on Cross-Disciplinary Designs and Applications of Automation 2022 DOI:10.4018/978-1-6684-3694-3.ch021

[3]	The pneumatic wheel model with plastic elements and force loss ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 2021 DOI:10.1002/zamm.202000091

[4]	Development Of Regression Models To Measure Energy And Inflation Time Of A Fabricated Tyre Pressure Control Unit International Journal of Automotive Science And Technology, 2021 DOI:10.30939/ijastech..927428

[5]	Development Of Regression Models To Measure Energy And Inflation Time Of A Fabricated Tyre Pressure Control Unit International Journal of Automotive Science and Technology, 2021 DOI:10.30939/ijastech..927428

[6]	Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing Advances in Business Information Systems and Analytics, 2020 DOI:10.4018/978-1-7998-2725-2.ch002

[7]	Innovative Material Characterisation Methodology for Tyre Static and Dynamic Analyses SAE Technical Paper Series, 2020 DOI:10.4271/2020-01-1519

[8]	Exploring Neural Network to Predict Car Tyre Inflation Time and Power Requirement of a Tyre Pressure Control Unit. Journal of Physics: Conference Series, 2019 DOI:10.1088/1742-6596/1378/3/032080

[9]	Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network Polymers, 2018 DOI:10.3390/polym10060644

[10]	Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling MATEC Web of Conferences, 2016 DOI:10.1051/matecconf/20168104012

[11]	FE-Based Tire Loading Estimation for Developing Strain-Based Intelligent Tire System SAE Technical Paper Series, 2015 DOI:10.4271/2015-01-0627

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journal of Intelligent Learning Systems and Applications

Journal of Intelligent Learning Systems and Applications

Journals Menu

Home

About SCIRP

Service

Policies