Applying neuro fuzzy system to analyze durian minerals within soil for precision agriculture

Name: Pongsarun Boonyopakorn

Organization : King Mongkut's University of Technology North Bangkok. Department of Data Communication and Networking

Email : pongsarunb@kmutnb.ac.th

Name: Pongtud Bualeard

Organization : King Mongkut's University of Technology North Bangkok. Department of Data Communication and Networking

Email : s6107031858150@email.kmutnb.ac.th

LCSH: Precision farming

LCSH: Soils -- Analysis

LCSH: Durian -- Harvesting

Abstract: The objective of this paper is to study precision farming for durian cultivation in Thailand by analyzing soil and environmental data within the plot, including mineral composition, soil pH, temperature, humidity, and sunlight. The dataset analyzed over the past five years consisted of 1,826 records. For data analysis, a neuro-fuzzy system algorithm is proposed to improve recommendation results and is compared with four algorithms: neural network, decision tree, k-nearest neighbor, and Naive Bayes. The results show that the neural network achieved a precision of 89.05%, the decision tree an accuracy of 84.12%, k-nearest neighbor an accuracy of 83.03%, and Naive Bayes an accuracy of 87.23%. The proposed neuro-fuzzy algorithm achieved the highest accuracy of 91.24%.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2020

Modified: 2026-03-31

Issued: 2026-03-31

บทความ/Article

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BibliograpyCitation : In Prince of Songkla University. College of Computing. The 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2020) (pp.135-138). Pattani : Prince of Songkla University

eng

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