期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：77
期号：1
出版社：Journal of Theoretical and Applied
摘要：Automation of essential processes in agriculture is becoming widespread, especially when fast action is required. However, some processes that could greatly benefit from some degree of automation have such difficult characteristics, that even small improvements pose a great challenge. This is the case of paddy disease diagnosis, a problem of great economic, social and ecological interest. Difficult problems like this often require a interdisciplinary approach to be tackled properly, as multifaceted issues can greatly benefit from the inclusion of different perspectives. In this context, this paper presents the most recent advances in research subjects such as data mining algorithm applied to paddy disease diagnosis, and give the solution, and discusses how those advances may be combined to support future developments towards more effective diagnosis tools. The paper finishes suggesting a possible solution to increase the degree of automation of paddy disease diagnosis tools.
关键词：Classification; Association Set Rules; K-Nearest Neighbor; Apriori Algorithm Artificial Neural
