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Proceedings of

International Conference on Recent Trends in Computing and Communication Engineering RTCCE 2013

"FISH STOCK PREDICTION USING DATA MINING AND IMAGE PROCESSING TECHNIQUES BASED ON SALINITY, TEMPERATURE AND CHLOROPHYLL DISTRIBUTION"

MADANA MOHANA R PRUDHVI KUMAR REDDY K RAMA MOHANA REDDY A
DOI
10.15224/978-981-07-6184-4-50
Pages
230 - 234
Authors
3
ISBN
978-981-07-6184-4

Abstract: “Agriculture is the main occupation of the people who are living in most of the developing and under developed countries. And People also depending on fish production for their livelihood. Fish stock estimation has been put forth by Marine societies, using the images sent by the satellites. But, this estimation sometimes fails due to the sudden changes in climatic conditions. The present paper has addressed the above problem. The main object of this paper is to predict the stock concentration with high accuracy rate. This paper mainly uses the concepts of image processing, data mining and strives for the development of a high accurate model. As the number of parameters has been increased, the accuracy of the model will be increased. The aim is to predict the correct geographical position of the fish stock concentration and will extended for several additional inclusions such as prediction of accurate fish number and type of fish etc.”

Keywords: Fish Stock, Image Processing, Data Mining, Prediction, Salinity, Ocean, Temperature, Satellite Images, Clustering.

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