Prediction of evaluation learning by using neuro-fuzzy system

Artificial intelligent techniques are being actively applied in many applications. With their powerful learning capability of neural networks and reducing the optimizing search space by prior knowledge rules of Fuzzy systems have been proven to be rather efficiency. In this research, the hybrid Neur...

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Main Authors: Rati Wonsathan, Isaravuth Seedadan, Nittaya Nunloon, Jesadapong Kitibut
Format: Book Series
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/53529
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-535292018-09-04T09:50:51Z Prediction of evaluation learning by using neuro-fuzzy system Rati Wonsathan Isaravuth Seedadan Nittaya Nunloon Jesadapong Kitibut Engineering Artificial intelligent techniques are being actively applied in many applications. With their powerful learning capability of neural networks and reducing the optimizing search space by prior knowledge rules of Fuzzy systems have been proven to be rather efficiency. In this research, the hybrid Neuro-Fuzzy system (NF) is proposed to be utilized as a predictor of the Grade Point Average (GPA) of students for future planning where the Radial Basis Function (RBF) is implemented as a neuro-fuzzy system. The NF's parameters consisted of centre and width of the Gaussian membership function and weight between input layer and output layer are automatically tuned by using Genetic Algorithms (GA) referred as NF-GA. The collected data is then tested and trained through NF-GA system with Minimum Mean Square Error (MMSE) technique. It has been shown that our proposed model is capable of prediction GPA by accurately 93%.The performance comparison between the proposed NF-GA and Multiple Regression Analysis (MRA) gives performance significantly by reducing the average error of the prediction down to 10%. © (2014) Trans Tech Publications, Switzerland. 2018-09-04T09:50:51Z 2018-09-04T09:50:51Z 2014-01-01 Book Series 10226680 2-s2.0-84901501871 10.4028/www.scientific.net/AMR.931-932.1482 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901501871&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53529
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Engineering
spellingShingle Engineering
Rati Wonsathan
Isaravuth Seedadan
Nittaya Nunloon
Jesadapong Kitibut
Prediction of evaluation learning by using neuro-fuzzy system
description Artificial intelligent techniques are being actively applied in many applications. With their powerful learning capability of neural networks and reducing the optimizing search space by prior knowledge rules of Fuzzy systems have been proven to be rather efficiency. In this research, the hybrid Neuro-Fuzzy system (NF) is proposed to be utilized as a predictor of the Grade Point Average (GPA) of students for future planning where the Radial Basis Function (RBF) is implemented as a neuro-fuzzy system. The NF's parameters consisted of centre and width of the Gaussian membership function and weight between input layer and output layer are automatically tuned by using Genetic Algorithms (GA) referred as NF-GA. The collected data is then tested and trained through NF-GA system with Minimum Mean Square Error (MMSE) technique. It has been shown that our proposed model is capable of prediction GPA by accurately 93%.The performance comparison between the proposed NF-GA and Multiple Regression Analysis (MRA) gives performance significantly by reducing the average error of the prediction down to 10%. © (2014) Trans Tech Publications, Switzerland.
format Book Series
author Rati Wonsathan
Isaravuth Seedadan
Nittaya Nunloon
Jesadapong Kitibut
author_facet Rati Wonsathan
Isaravuth Seedadan
Nittaya Nunloon
Jesadapong Kitibut
author_sort Rati Wonsathan
title Prediction of evaluation learning by using neuro-fuzzy system
title_short Prediction of evaluation learning by using neuro-fuzzy system
title_full Prediction of evaluation learning by using neuro-fuzzy system
title_fullStr Prediction of evaluation learning by using neuro-fuzzy system
title_full_unstemmed Prediction of evaluation learning by using neuro-fuzzy system
title_sort prediction of evaluation learning by using neuro-fuzzy system
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901501871&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/53529
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