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)|
|Deposited By:||Maznira Sylvia Azra Mansor|
|Deposited On:||09 Jan 2009 01:52|
|Last Modified:||01 Jun 2010 15:53|
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