Multi-Adaptive Neuro-Fuzzy Inference System for Dielectric Properties of Oil Palm Fruitlets

Accurate dielectric models are required for proper sensing and characterization of materials especially for the purpose of quality control. In this work, a multi-Adaptive Neuro-Fuzzy Inference System (ANFIS) was designed to model the complex permittivity of the mesocarps of oil palm fruitlets within...

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Published inInternational Journal of Applied Science and Engineering Vol. 12; no. 1; pp. 001 - 008
Main Authors Ojo O. Adedayo, M. M. Isa, A. Che Soh, Z. Abbas
Format Journal Article
LanguageChinese
Published 台灣 朝陽科技大學理工學院 01.03.2014
Subjects
ANFIS
dielectric properties
oil palm fruitlets
Scopus
sensing
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Abstract Accurate dielectric models are required for proper sensing and characterization of materials especially for the purpose of quality control. In this work, a multi-Adaptive Neuro-Fuzzy Inference System (ANFIS) was designed to model the complex permittivity of the mesocarps of oil palm fruitlets within the frequency range of 2-4GHz. The system consists of two ANFIS models with same sets of inputs; one ANFIS model for the dielectric constant and the other for the loss factor. Training data were obtained from laboratory microwave measurements with the aid of Vector Network Analyzer (VNA) and used for the ANFIS model. The evaluation of the performance of the model confirms the suitability of the multi-ANFIS model for rapid and accurate determination of the dielectric properties of the fruitlets.
AbstractList Accurate dielectric models are required for proper sensing and characterization of materials especially for the purpose of quality control. In this work, a multi-Adaptive Neuro-Fuzzy Inference System (ANFIS) was designed to model the complex permittivity of the mesocarps of oil palm fruitlets within the frequency range of 2-4GHz. The system consists of two ANFIS models with same sets of inputs; one ANFIS model for the dielectric constant and the other for the loss factor. Training data were obtained from laboratory microwave measurements with the aid of Vector Network Analyzer (VNA) and used for the ANFIS model. The evaluation of the performance of the model confirms the suitability of the multi-ANFIS model for rapid and accurate determination of the dielectric properties of the fruitlets.
Author Ojo O. Adedayo
Z. Abbas
A. Che Soh
M. M. Isa
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Snippet Accurate dielectric models are required for proper sensing and characterization of materials especially for the purpose of quality control. In this work, a...
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SubjectTerms ANFIS
dielectric properties
oil palm fruitlets
Scopus
sensing
Title Multi-Adaptive Neuro-Fuzzy Inference System for Dielectric Properties of Oil Palm Fruitlets
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