DISCOVERY OF CROPPING REGIONS DUE TO GLOBAL CLIMATIC CHANGES USING DATA MINING
This paper focuses an intelligent tool AgroAdvisor that is developed to measure the probability of success of crops on the basis of a set of environmental factors. The tool is being trained to capture climatic change impact on different cropping regions. The success of a crop is dependent on a large number of factors including rainfall, soil type, temperature etc. Bayesian model is used for the development of this tool, which is capable of predicting behavior of crops under different climatic conditions on the basis of history. Results of AgroAdvisor have been verified for cotton cropping regions under prevailing climatic conditions. Training of AgroAdvisor to cater climatic change impact is based on a hypothetical model of global climatic change. However, it has been verified that in the presence of original model it can be trusted for its results.
Global climatic change Bayesian modeling Cotton Cropping regions
Ahsan Abdullah
Imran Ahmed Ansari Center for Agro-Informatics Research National University of Computer & Emerging Sciences FAST House, Rohtas Road G-9/4, Islamabad, Pakistan
国际会议
北京
英文
3-11
2005-10-14（万方平台首次上网日期，不代表论文的发表时间）