NDLI: The optimal fuzzy c-regression models (OFCRM) in miles per gallon of cars prediction

Content Provider	IEEE Xplore Digital Library
Author	Rusiman, M.S. Nasibov, E. Adnan, R.
Copyright Year	2011
Description	Author affiliation: Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia (Rusiman, M.S.) \|\| Dokuz Eylul University, Turkey (Nasibov, E.) \|\| Universiti Teknologi Malaysia (UTM), Malaysia (Adnan, R.)
Abstract	The fuzzy c-regression models (FCRM) have been known to be used in order to fit models with a certain type of mixed data. In this study, we proposed new optimal FCRM models (OFCRM). In order to obtain the least mean square error (MSE), we proposed modification of $w^{i}(x),$ the backward elimination method and the adjustment of the fuzzifier (w). The $w^{i}(x)$ is found by using the matrix Wi in weighted least-square (WLS) method. The backward elimination method is used in the variable selection in the OFCRM models, whereas the fuzzifier, w is adjusted by putting in various values of w (between 1 and 3). The OFCRM models are tested to the simulated data and the OFCRM models can approximate the given nonlinear system with a higher accuracy. In this study, the fuel consumption of different cars in miles per gallon (MPG) with eight independent variables were predicted using the OFCRM models. It was found that all variables are significant and w= 1.502 is the best fuzzifier value to be used in OFCRM models. The comparison among multiple linear regression (MLR) model, FCRM models and OFCRM models were done to find the best model by using the mean square error (MSE). It was found that the OFCRM models with the lowest MSE (MSE=3.106) tends to be the best model if compared to the MLR model (MSE=8.24) and FCRM models (MSE=7.848). This new technique has been found to have great capabilities and more reliable in predicting the dependent variable.
Starting Page	333
Ending Page	338
File Size	1197022
Page Count	6
File Format	PDF
ISBN	9781467300995
e-ISBN	9781467301022
DOI	10.1109/SCOReD.2011.6148760
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-19
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy c-regression models (FCRM) mean square error (MSE) optimal FCRM models (OFCRM) Reliability multiple linear regression (MLR) model
Content Type	Text
Resource Type	Article

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