Explorations of a Bayesian Belief Network for the Simultaneous Farming of Rice and Shrimp Crops

Andrew Lewis, Marcus Randall, Ben Stewart-Koster, Anh Dieu Nguyen, Michele Astrid Burford, Jason Condon, Nguyen Van Qui, Le Huu Hiep, Doan Van Bay, Jesmond Sammut

Research output: Book chapter/Published conference paperConference paperpeer-review


Efficiencies in farming practice in many parts of South East Asia can make substantial, positive differences to villages and communities. The use of automated decision-assistance tools such as Bayesian Belief Networks (BBNs) can help to accomplish this. For the problem described herein, farmers attempt to grow both rice and shrimp crops in the same physical area. The motivation becomes one of finding a set of conditions that minimises the probabilities of crop failures. In this work, we explore an existing BBN and determine a range of likely environmental scenarios and the factors that farmers can control to help improve the likelihood of harvesting successful rice and shrimp crops.
Original languageEnglish
Title of host publication16th International Conference on Computer Applications
Subtitle of host publicationICCA 2018
Number of pages19
Publication statusPublished - Apr 2018
Event16th International Conference on Computer Applications: ICCA 2018 - Sedona Hotel, Yangon, Myanmar
Duration: 22 Feb 201823 Feb 2018


Conference16th International Conference on Computer Applications
Internet address

Fingerprint Dive into the research topics of 'Explorations of a Bayesian Belief Network for the Simultaneous Farming of Rice and Shrimp Crops'. Together they form a unique fingerprint.

Cite this