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An intelligent system based on kernel methods for crop yield prediction

Majid Awan, A and Sap, M.N Md (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


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:01 Jun 2010 15:53

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