STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition

STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition

© 2017 IEEE. This study aims at providing a hybrid knowledge acquisition approach with fuzzy machine learning technique which assists to obtain knowledge when constructing expert systems. The study defines the knowledge acquisition framework that has been developed in order to make it easier and to...

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Main Authors: Jirawit Yanchinda, Thepparit Sinthamrongruk, Keshav Dahal
Format: Conference Proceeding
Published: 2018
Subjects:
Computer Science
Decision Sciences
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85054203588&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/62665
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Institution: Chiang Mai University
id th-cmuir.6653943832-62665
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spelling th-cmuir.6653943832-626652018-11-29T07:40:01Z STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition Jirawit Yanchinda Thepparit Sinthamrongruk Keshav Dahal Computer Science Decision Sciences © 2017 IEEE. This study aims at providing a hybrid knowledge acquisition approach with fuzzy machine learning technique which assists to obtain knowledge when constructing expert systems. The study defines the knowledge acquisition framework that has been developed in order to make it easier and to provide appropriate interpretations for organic rice farmers and build inferential knowledge based on STEM learning concept in a fuzzy rule representation framework. The main concentration of this study is to demonstrate the knowledge acquisition technique as a method for extending, modernizing and improving a defective knowledge based-system in which fuzzy machine learning is beneficial. 2018-11-29T07:38:44Z 2018-11-29T07:38:44Z 2018-02-16 Conference Proceeding 25733214 2373082X 2-s2.0-85054203588 10.1109/SKIMA.2017.8294113 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85054203588&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62665
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Decision Sciences
spellingShingle Computer Science
Decision Sciences
Jirawit Yanchinda
Thepparit Sinthamrongruk
Keshav Dahal
STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition
description © 2017 IEEE. This study aims at providing a hybrid knowledge acquisition approach with fuzzy machine learning technique which assists to obtain knowledge when constructing expert systems. The study defines the knowledge acquisition framework that has been developed in order to make it easier and to provide appropriate interpretations for organic rice farmers and build inferential knowledge based on STEM learning concept in a fuzzy rule representation framework. The main concentration of this study is to demonstrate the knowledge acquisition technique as a method for extending, modernizing and improving a defective knowledge based-system in which fuzzy machine learning is beneficial.
format Conference Proceeding
author Jirawit Yanchinda
Thepparit Sinthamrongruk
Keshav Dahal
author_facet Jirawit Yanchinda
Thepparit Sinthamrongruk
Keshav Dahal
author_sort Jirawit Yanchinda
title STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition
title_short STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition
title_full STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition
title_fullStr STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition
title_full_unstemmed STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition
title_sort stem learning concept with fuzzy inference for organic rice farming knowledge acquisition
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85054203588&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/62665
_version_ 1681425849378668544

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