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An intelligent system based on kernel methods for crop yield prediction

Majid Awan, A. and Md. Sap, Mohd. Noor (2006) An intelligent system based on kernel methods for crop yield prediction. In: Lecture Notes in Computer Science(including subseries Lecture Notes in Artificial Intelligent and Lecture Notes in Bioinformatics) .

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Official URL: http://dx.doi.org/10.1007/11731139_98

Abstract

This paper presents work on developing a software system for predicting crop yield from climate and plantation data. At the core of this system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. For this purpose, a robust weighted kernel k-means algorithm incorporating spatial constraints is presented. The algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:7573
Deposited By: Maznira Sylvia Azra Mansor
Deposited On:09 Jan 2009 01:52
Last Modified:24 Aug 2017 04:24

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