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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/6210/1/Terramechanics.pdf
http://irep.iium.edu.my/6210/4/IACTV-_2012.pdf
http://irep.iium.edu.my/6210/
http://www.sciencedirect.com/science/article/pii/S0022489811000577
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spelling my.iium.irep.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 REM 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
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
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/6210/1/Terramechanics.pdf
http://irep.iium.edu.my/6210/4/IACTV-_2012.pdf
http://irep.iium.edu.my/6210/
http://www.sciencedirect.com/science/article/pii/S0022489811000577
_version_ 1643605686546857984
score 13.211869

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