Temperature Prediction based on Artificial Neural Network and its Impact on Rice Production, Case Study: Bangladesh

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International Journal of Computer Applications
© 2011 by IJCA Journal
Number 1 - Article 1
Year of Publication: 2011
Authors:
Tushar Kanti Routh
Md. Monsurul Huda
10.5120/3941-5540

Tushar Kanti Routh and Md. Monsurul Huda. Article:Temperature Prediction based on Artificial Neural Network and its Impact on Rice Production, Case Study: Bangladesh. International Journal of Computer Applications 31(11):23-28, October 2011. Full text available. BibTeX

@article{key:article,
	author = {Tushar Kanti Routh and Md. Monsurul Huda},
	title = {Article:Temperature Prediction based on Artificial Neural Network and its Impact on Rice Production, Case Study: Bangladesh},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {31},
	number = {11},
	pages = {23-28},
	month = {October},
	note = {Full text available}
}

Abstract

Potential rise of global temperature due to climate change has huge impact on rice productivity and above all on food security. The variation of temperature along with diverse climatic phenomena like cyclone, drought and changing rainfall patterns cause significant loss in food grain production every year. Although weather prediction and meteorology is a very complex and imprecise science, recent research activities with Artificial Neural Net¬work (ANN) have shown that it has powerful pattern classification and pattern recognition capa¬bilities which can be used as a tool to get a reasonable accurate prediction of weather patterns. In this paper, an ANN model based on Multilayer Perceptron concept has been developed and trained using backpropagation learning algorithm to estimate the Daily Mean, Maximum and Minimum temperature of Dhaka, capital of Bangladesh..The result shows that Neural Network can be used for temperature prediction successfully.

Reference

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