Theoretical framework towards Crop Yield Classification using Fuzzy SQL and Fuzzy Relational Database

Kile, Awuna Samuel, Ukeyima, Dooshima Joyce, Adegoke, O. Folake

Abstract: Inefficient classification of agricultural products has resulted to failure or poor market value for many crops. The need for using technology in enhancing crop yield classification cannot be overemphasized. This work used fuzzy logic system in performing crop yield classification and considered yam for the representation. Attributes of yam like size, length, age, date of maturity, and others are considered in this work. Fuzzy rules for the classification are formed. A fuzzy SQL expression using Create, Insert, Select and Classify statements for the implementation are considered. The evaluation shows that classifying crop yield using fuzzy systems adds great value to post harvest yield management and enhances crops marketing and storage value with high efficiency.  

Keywords: Crop Yield, Fuzzy Classification, Fuzzy Logic, SQL, System.

Title: Theoretical framework towards Crop Yield Classification using Fuzzy SQL and Fuzzy Relational Database

Author: Kile, Awuna Samuel, Ukeyima, Dooshima Joyce, Adegoke, O. Folake

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 29-36

Research Publish Journals

Website: www.researchpublish.com

Published Date: 03-November-2023

DOI: https://doi.org/10.5281/zenodo.10068420

Vol. 11, Issue 4, October 2023 - December 2023

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Theoretical framework towards Crop Yield Classification using Fuzzy SQL and Fuzzy Relational Database by Kile, Awuna Samuel, Ukeyima, Dooshima Joyce, Adegoke, O. Folake