Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation

This paper presents the fuzzy logic expert system (FLES) for an intelligent air-cushion tracked vehicle performance investigation operating on swamp peat terrain. Compared with traditional logic model, fuzzy logic is more efficient in linking the multiple units to a single output and is invaluable s...

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Main Authors:	Hossain, Altab, Rahman, Mohammed Ataur, Mohiuddin, A. K. M.
Format:	Article
Language:	English English
Published:	Elsevier Ltd. 2011
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/6210/ http://irep.iium.edu.my/6210/ http://irep.iium.edu.my/6210/ http://irep.iium.edu.my/6210/1/Terramechanics.pdf http://irep.iium.edu.my/6210/4/IACTV-_2012.pdf

id	iium-6210
recordtype	eprints
spelling	iium-62102014-06-04T16:16:24Z http://irep.iium.edu.my/6210/ Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation Hossain, Altab Rahman, Mohammed Ataur Mohiuddin, A. K. M. T Technology (General) This paper presents the fuzzy logic expert system (FLES) for an intelligent air-cushion tracked vehicle performance investigation operating on swamp peat terrain. Compared with traditional logic model, fuzzy logic is more efficient in linking the multiple units to a single output and is invaluable supplements to classical hard computing techniques. Therefore, the main purpose of this study is to investigate the relationship between vehicle working parameters and performance characteristics, and to evaluate how fuzzy logic expert system plays an important role in prediction of vehicle performance. Experimental values are taken in the swamp peat terrain for vehicle performance investigation. In this paper, a fuzzy logic expert system model, based on Mamdani approach, is developed to predict the tractive efficiency and power consumption. Verification of the developed fuzzy logic model is carried out through various numerical error criteria. For all parameters, the relative error of predicted values are found to be less than the acceptable limits (10%) and goodness of fit of the predicted values are found to be close to 1.0 as expected and hence shows the good performance of the developed system. Elsevier Ltd. 2011 Article PeerReviewed application/pdf en http://irep.iium.edu.my/6210/1/Terramechanics.pdf application/pdf en http://irep.iium.edu.my/6210/4/IACTV-_2012.pdf Hossain, Altab and Rahman, Mohammed Ataur and Mohiuddin, A. K. M. (2011) Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation. Journal of Terramechanics. ISSN 0022-4898 http://www.sciencedirect.com/science/article/pii/S0022489811000577 DOI: 10.1016/j.jterra.2011.08.002
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Hossain, Altab Rahman, Mohammed Ataur Mohiuddin, A. K. M. Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
description	This paper presents the fuzzy logic expert system (FLES) for an intelligent air-cushion tracked vehicle performance investigation operating on swamp peat terrain. Compared with traditional logic model, fuzzy logic is more efficient in linking the multiple units to a single output and is invaluable supplements to classical hard computing techniques. Therefore, the main purpose of this study is to investigate the relationship between vehicle working parameters and performance characteristics, and to evaluate how fuzzy logic expert system plays an important role in prediction of vehicle performance. Experimental values are taken in the swamp peat terrain for vehicle performance investigation. In this paper, a fuzzy logic expert system model, based on Mamdani approach, is developed to predict the tractive efficiency and power consumption. Verification of the developed fuzzy logic model is carried out through various numerical error criteria. For all parameters, the relative error of predicted values are found to be less than the acceptable limits (10%) and goodness of fit of the predicted values are found to be close to 1.0 as expected and hence shows the good performance of the developed system.
format	Article
author	Hossain, Altab Rahman, Mohammed Ataur Mohiuddin, A. K. M.
author_facet	Hossain, Altab Rahman, Mohammed Ataur Mohiuddin, A. K. M.
author_sort	Hossain, Altab
title	Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
title_short	Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
title_full	Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
title_fullStr	Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
title_full_unstemmed	Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
title_sort	fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation
publisher	Elsevier Ltd.
publishDate	2011
url	http://irep.iium.edu.my/6210/ http://irep.iium.edu.my/6210/ http://irep.iium.edu.my/6210/ http://irep.iium.edu.my/6210/1/Terramechanics.pdf http://irep.iium.edu.my/6210/4/IACTV-_2012.pdf
first_indexed	2023-09-18T20:15:03Z
last_indexed	2023-09-18T20:15:03Z
_version_	1777407731842416640

Fuzzy evaluation for an intelligent air-cushion tracked vehicle performance investigation

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