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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Main Authors: Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly
Format: Article
Published: Chaoyang University of Technology 2014
Online Access:http://psasir.upm.edu.my/id/eprint/34606/
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author Adedayo, Ojo O.
Mohd Isa, Maryam
Che Soh, Azura
Abbas, Zulkifly
author_facet Adedayo, Ojo O.
Mohd Isa, Maryam
Che Soh, Azura
Abbas, Zulkifly
author_sort Adedayo, Ojo O.
building UPM Institutional Repository
collection Online Access
description 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.
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spelling upm-346062015-12-16T04:14:57Z http://psasir.upm.edu.my/id/eprint/34606/ Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets Adedayo, Ojo O. Mohd Isa, Maryam Che Soh, Azura Abbas, Zulkifly 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. Chaoyang University of Technology 2014 Article PeerReviewed Adedayo, Ojo O. and Mohd Isa, Maryam and Che Soh, Azura and Abbas, Zulkifly (2014) Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets. International Journal of Applied Science and Engineering, 12 (1). pp. 1-8. ISSN 1727-2394; ESSN: 1727-7841 http://www.cyut.edu.tw/~ijase/2014/12%281%29/12%281%29-1_028011_en.htm
spellingShingle Adedayo, Ojo O.
Mohd Isa, Maryam
Che Soh, Azura
Abbas, Zulkifly
Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets
title Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets
title_full Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets
title_fullStr Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets
title_full_unstemmed Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets
title_short Multi-adaptive Neuro-Fuzzy Inference System for dielectric properties of oil palm fruitlets
title_sort multi-adaptive neuro-fuzzy inference system for dielectric properties of oil palm fruitlets
url http://psasir.upm.edu.my/id/eprint/34606/
http://psasir.upm.edu.my/id/eprint/34606/