DSpace
 

iRepository at Perpustakaan UniMAP >
Journal Articles >
School of Computer and Communication Engineering (Articles) >

Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/6973

Title: Rice yield classification using Backpropagation Network
Authors: Puteh, Saad
Nor Khairah, Jamaludin
Siti Sakira, Kamrudin
Aryati, Bakri
Nursalasawati, Rusli
Keywords: Backpropagation network;Classification;Rice yield;Pests;Diseases;Weeds;Neural networks (Computer science);Computer programming;Back propagation
Issue Date: 2004
Publisher: Penerbit Universiti Utara Malaysia
???metadata.dc.publisher.department???: Fakulti Teknologi Maklumat
Citation: Journal of ICT, vol.3(1), 2004, pages 67-81.
Abstract: Among factors that affect rice yield area are diseases, pests and weeds. It is intractable to model the correlation between plant diseases, pests and weeds on the amount of rice yield statistically and mathematically. In this study, a backpropagation network (BPN) is developed to classify rice yield based on the aforementioned factors in MUDA irrigation area Malaysia. The result of this study showns that BPN is able to classify the rice yield to a deviation of 0.03.
Description: Link to publisher's homepage at www.jict.uum.edu.my
URI: http://hdl.handle.net/123456789/6973
Appears in Collections:School of Computer and Communication Engineering (Articles)

Files in This Item:

File Description SizeFormat
Rice Yield Classification Using Backpropagation Network.pdfAccess is limited to UniMAP community.5.59 MBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! Perpustakaan Tuanku syed Faizuddin Putra, Kampus Pauh Putra, Universiti Malaysia Perlis, 02600, Arau Perlis
TEL: +604-9885420 | FAX: +604-9885405 | EMAIL: rujukan@unimap.edu.my Feedback