Abstract
In this paper, we propose an effective rice crop planning system based on a knowledge engineering approach with hybrid knowledge representation, i.e., ontologies and rules, to help farmers make decisions in choosing their rice variety and planning cultivation. A critical challenge is to develop a recommendation system that supports and fulfills farmers' satisfaction, i.e., reducing risk from climate conditions and disease while improving productivity to meet market demand. To fulfill these needs, our recommendation system is separated into two parts: a rice variety suggestion system, which will help to suggest which variety to grow; and a personalized crop calendar generation system, which will help farmers in planning their activities toward higher production.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.