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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/288

Title: Agricultural Prediction and Decision Support System for Sri Lanka
Authors: De Silva, A.G.D.D.
De Silva, G.N.N.
Wijesinghe, A.J.A.
Waas, M.W.P.K.
Haddela, P.S.
Perera, Ajith
Keywords: ARIMA Model
Optimization
Data Warehousing
Time Series Analysis
Crop Selection
Issue Date: Dec-2014
Publisher: SLIIT
Series/Report no.: NCTM 2014;06
Abstract: In Sri Lanka, Information Technology is rarely used in agricultural decision making processes compared to other fields. Therefore technological advancement of an accurate and a centralized decision making process has been aroused since many decades. APDSS is implemented by focusing on major irrigation areas in dry zone. In major irrigation areas, selection of crops for cultivation in the upcoming season are mostly done, based on the available water amounts in the reservoirs. APDSS is mainly implemented to support crop selection decision making in agricultural management and maximize the productivity by utilizing available resources at a maximum level. This system is capable to preform crop combination selection by considering dependent factors like water levels in reservoirs, rainfall, cultivatable extent and fertilizer subsidy, while maximizing the profitability. In the approach to determine most suitable crop combination to cultivate in profitability point of view, system itself predicts the possible yield outcomes of five different crops for available conditions like rainfall, water issue of the reservoirs and also predicts cultivation costs and farm gate prices for each crop by considering factors like fertilizer usage. Crop selection module has been implemented with the use of mathematical optimization functions and yield and profit prediction modules have been implemented by past data analysis with the use of time series algorithms with the aid of centralized data warehouse.
URI: http://hdl.handle.net/123456789/288
ISSN: 18003591
Appears in Collections:NCTM - SLIIT 2014 -DECEMBER

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