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General Information
    • ISSN: 1793-8198
    • Frequency: Quarterly
    • DOI: 10.18178/IJMMM
    • Editor-in-Chief: Prof. K. M. Gupta, Prof. Ian McAndrew
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/Indexing: EI (INSPEC, IET), Chemical Abstracts Services (CAS), Engineering & Technology Digital Library,  ProQuest, Crossref, Ulrich's Periodicals Directory, DOAJ, and Electronic Journals Library .
    • E-mail ijmmm@ejournal.net
Editor-in-chief
Prof. Ian McAndrew
Embry Riddle Aeronautical University, UK.
It is my honor to be the editor-in-chief of IJMMM. I will do my best to help develop this journal better.

IJMMM 2015 Vol.3(3): 213-217 ISSN: 1793-8198
DOI: 10.7763/IJMMM.2015.V3.199

Role of Input Selection Prediction of Physical Properties of Degradable Composites Using ANFIS

Syamsiah Abu Bakar, Rosma Mohd Dom, Ajab Bai Akbarally, and Wan Hasamudin Wan Hassan
Abstract—ANFIS employ multi-input single-output (MISO) system. This paper proposes role of input selection using neuro-fuzzy approach for the prediction of physical properties of degradable composites namely melt flow index and density. Experiments on the physical properties of degradable composites are currently carried out in the laboratories of Malaysian Palm Oil Board. ANFIS simulation provides good alternative method for minimize the time consumed, the cost of production and the cost of labour on the production of degradable composites. The results reveal that, all the input selection give high prediction accuracy by smallest Root Mean Square Error (RMSE) values and high correlation coefficient (R), coefficient of determination (2R) and adjusted R square (2R). These findings give additional evidence that ANFIS has high ability on input selection in the prediction of degradable composites.

Index Terms—ANFIS, degradable composites, input selection, physical properties.

Syamsiah Abu Bakar is with the University Kuala Lumpur Malaysia France Institute, Malaysia (e-mail: syamsiah@unikl.edu.my).
Rosma Mohd Dom and Ajab Bai Akbarally are with the Universiti Technology Mara, Malaysia (e-mail: rosma@tmsk.uitm.edu.my, ajab@tmsk.uitm.edu.my).
Wan Hasamudin Wan Hassan is with the Biomass Technology Centre, Engineering & Processing Division, MPOB, Malaysia (e-mail: wanhaswh@mpob.gov.my).

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Cite: Syamsiah Abu Bakar, Rosma Mohd Dom, Ajab Bai Akbarally, and Wan Hasamudin Wan Hassan, "Role of Input Selection Prediction of Physical Properties of Degradable Composites Using ANFIS," International Journal of Materials, Mechanics and Manufacturing vol. 3, no. 3, pp. 213-217, 2015.

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