With the advent of modern computer technology, the field of Artificial Intelligence is playing a significant role in improving almost every spectrum of human life. In the field of agriculture, there is always need for optimality with improved crop yield. This paper dwells majorly on the application of fuzzy logic to predict crop type with optimal crop yield based on available soil nutrients. Some soil data samples were collected from the department of soil science, Federal University of Agriculture, Abeokuta and used as input into the system. The proposed system was simulated using MatLab Fuzzy inference System with a triangular member function. The range of nutrients was later deployed as input into a visual basic developed application to predict the best crop to be planted. A dual method (static and dynamic) was used in testing and validating the result of research which showed a significant improvement on the crop type selection than the conventional prediction mode
Johnson, F. (2020). A fuzzy-Based Decision Support System for Soil Selection in Olericulture. Afribary. Retrieved from https://afribary.com/works/a-fuzzy-based-decision-support-system-for-soil-selection-in-olericulture
Johnson, Femi "A fuzzy-Based Decision Support System for Soil Selection in Olericulture" Afribary. Afribary, 19 Jun. 2020, https://afribary.com/works/a-fuzzy-based-decision-support-system-for-soil-selection-in-olericulture. Accessed 25 Dec. 2024.
Johnson, Femi . "A fuzzy-Based Decision Support System for Soil Selection in Olericulture". Afribary, Afribary, 19 Jun. 2020. Web. 25 Dec. 2024. < https://afribary.com/works/a-fuzzy-based-decision-support-system-for-soil-selection-in-olericulture >.
Johnson, Femi . "A fuzzy-Based Decision Support System for Soil Selection in Olericulture" Afribary (2020). Accessed December 25, 2024. https://afribary.com/works/a-fuzzy-based-decision-support-system-for-soil-selection-in-olericulture