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Manuscript Title: Pest Clustering With Self Organizing Map for Rice Productivity

Author : Shafaatunnur Hasan and Mohd Noor Md Sap

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Abstract: Rice, Oryza sativa, also known as paddy rice is produced by at least 95 countries around the globe with China and India are the largest producers of rice in the world; while Thailand, Vietnam and America are the largest world rice exporters. To sustain rice productivity, advance agriculture technologies have always been deployed to increase the productivity of this food grain. This is due to the pressure for high productivity and plant pests’ attacks. Geographical Information Systems (GIS) and Global Positioning Systems (GPS) have been used for variable rate application of pesticides, herbicide and fertilizers in Precision Agriculture applications. However, due to the weather uncertainties that affect the rice growth, intelligent solutions have been integrated in current pest management practices. Therefore, this study presents intelligent solutions by implementing spatial analysis and Kohonen Self Organizing Map (SOM) to cluster types of pests for better agricultural rice pest management in Malaysia.

Keywords: Genetic Algorithms, Classification methods, Confusion matrix, Fitness function, and Crossover.

Vol 2 (2)