An Intelligent System Based on Kernel Methods for Crop Yield Prediction

  • A. Majid Awan
  • Mohd. Noor Md. Sap
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3918)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • A. Majid Awan
    • 1
  • Mohd. Noor Md. Sap
    • 1
  1. 1.Faculty of Computer Sci. & Information SystemsUniversity Technology MalaysiaSkudai, JohorMalaysia

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