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Advances in Knowledge Discovery and Data Mining

Volume 3918 of the series Lecture Notes in Computer Science pp 841-846

An Intelligent System Based on Kernel Methods for Crop Yield Prediction

  • A. Majid AwanAffiliated withFaculty of Computer Sci. & Information Systems, University Technology Malaysia
  • , Mohd. Noor Md. SapAffiliated withFaculty of Computer Sci. & Information Systems, University Technology Malaysia

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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.