%0 Journal Article
%T Pest Clustering With Self Organizing Map for Rice Productivity
%A Shafaatunnur Hasan
%A Mohd Noor Md Sap
%J International Journal of Advances in Soft Computing and Its Applications
%D 2010
%I International Center for Scientific Research and Studies
%X Rice, Oryza sativa, also known as paddy rice is produced by atleast 95 countries around the globe with China and India are thelargest producers of rice in the world; while Thailand, Vietnam andAmerica are the largest world rice exporters. To sustain riceproductivity, advance agriculture technologies have always beendeployed to increase the productivity of this food grain. This is due tothe pressure for high productivity and plant pestsĄŻ attacks.Geographical Information Systems (GIS) and Global PositioningSystems (GPS) have been used for variable rate application ofpesticides, herbicide and fertilizers in Precision Agricultureapplications. However, due to the weather uncertainties that affectthe rice growth, intelligent solutions have been integrated in currentpest management practices. Therefore, this study presents intelligentsolutions by implementing spatial analysis and Kohonen SelfOrganizing Map (SOM) to cluster types of pests for betteragricultural rice pest management in Malaysia.
%K Rice
%K Clustering
%K Neural Network
%K Kohonen Self Organizing Map (SOM)
%U http://www.i-csrs.org/Volumes/ijasca/vol.2/vol.2.2.6.July.10.pdf