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Data mining on climatic factors for Harumanis mango yield prediction

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Main Authors: Rohani S., Mohamed Farook, Abdul Halis, Abdul Aziz, Azmi, Harun, Zulkifli, Husin, Ali Yeon, Md Shakaff, Prof. Dr.
Other Authors: rohani@unimap.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2013
Subjects:
Data mining
Mango yield prediction model
Regression
Soft computing
Harumanis
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/26052
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spelling my.unimap-260522013-06-25T04:39:59Z Data mining on climatic factors for Harumanis mango yield prediction Rohani S., Mohamed Farook Abdul Halis, Abdul Aziz Azmi, Harun Zulkifli, Husin Ali Yeon, Md Shakaff, Prof. Dr. rohani@unimap.edu.my Data mining Mango yield prediction model Regression Soft computing Harumanis Link to publisher's homepage at http://ieeexplore.ieee.org/ Yield Prediction is an essential task to be achieved in order to implement effective forward marketing. Forward marketing is a contract that will be signed between supplier and client based on the amount of delivery and the price of delivery in future. To be able to sign such a contract the supplier should be very confident that the yield could be achieved. The yield sustainability is a challenging process in agriculture. Mango cultivar Harumanis is one of the best table tropical fruit due to its aroma and sweetness. Despite its overwhelming local demand in Malaysia and also internationally, the fruit supply never meets the demand. The flowering phase is identified as an important stage as plant reproductive physiology. Currently, Harumanis mango flowering only happens once a year that restricts the yield. In this paper, data mining is used to quantify the climatic effects on Harumanis mango yield to enable yield prediction. 2013-06-25T04:39:59Z 2013-06-25T04:39:59Z 2012 Working Paper p. 115-119 978-076954668-1 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6169685 http://hdl.handle.net/123456789/26052 en Proceedings of the Intelligent Systems, Modelling and Simulation (ISMS) 2012 Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Data mining
Mango yield prediction model
Regression
Soft computing
Harumanis
spellingShingle Data mining
Mango yield prediction model
Regression
Soft computing
Harumanis
Rohani S., Mohamed Farook
Abdul Halis, Abdul Aziz
Azmi, Harun
Zulkifli, Husin
Ali Yeon, Md Shakaff, Prof. Dr.
Data mining on climatic factors for Harumanis mango yield prediction
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 rohani@unimap.edu.my
author_facet rohani@unimap.edu.my
Rohani S., Mohamed Farook
Abdul Halis, Abdul Aziz
Azmi, Harun
Zulkifli, Husin
Ali Yeon, Md Shakaff, Prof. Dr.
format Working Paper
author Rohani S., Mohamed Farook
Abdul Halis, Abdul Aziz
Azmi, Harun
Zulkifli, Husin
Ali Yeon, Md Shakaff, Prof. Dr.
author_sort Rohani S., Mohamed Farook
title Data mining on climatic factors for Harumanis mango yield prediction
title_short Data mining on climatic factors for Harumanis mango yield prediction
title_full Data mining on climatic factors for Harumanis mango yield prediction
title_fullStr Data mining on climatic factors for Harumanis mango yield prediction
title_full_unstemmed Data mining on climatic factors for Harumanis mango yield prediction
title_sort data mining on climatic factors for harumanis mango yield prediction
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/26052
_version_ 1643794822763380736
score 13.222552

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