A fuzzy rule base system for mango ripeness classification / Ab Razak Mansor ...[et al.]
Fuzzy rule base systems have been successfully applied to various classification problems due to its powerful capabilities of handling uncertainty and vagueness. This paper presents a fuzzy rule based system for the mango ripeness classification. The input and output of the system were RGB color and...
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2015-11-04.
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| LEADER | 00000 am a22000003u 4500 | ||
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| 001 | repouitm_54359 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Mansor, Ab Razak |e author |
| 700 | 1 | 0 | |a Othman, Mahmod |e author |
| 700 | 1 | 0 | |a Ali, Noor Rasidah |e author |
| 700 | 1 | 0 | |a Ahmad, Khairul Adilah |e author |
| 700 | 1 | 0 | |a Jamel Elias, Samsul |e author |
| 245 | 0 | 0 | |a A fuzzy rule base system for mango ripeness classification / Ab Razak Mansor ...[et al.] |
| 260 | |c 2015-11-04. | ||
| 500 | |a https://ir.uitm.edu.my/id/eprint/54359/1/54359.pdf | ||
| 520 | |a Fuzzy rule base systems have been successfully applied to various classification problems due to its powerful capabilities of handling uncertainty and vagueness. This paper presents a fuzzy rule based system for the mango ripeness classification. The input and output of the system were RGB color and mango ripeness classification. In the process of fuzzification, crisp inputs are fuzzified using selected membership functions. This study attempted to decide the most suitable membership function to obtain accurate output. Three types of membership functions such as Gaussian, Triangular and Trapezoidal have been compared. The result shows that the Triangular membership function gave higher accuracy than other membership functions. | ||
| 546 | |a en | ||
| 690 | |a Technological innovations | ||
| 690 | |a Agricultural industries | ||
| 655 | 7 | |a Conference or Workshop Item |2 local | |
| 655 | 7 | |a PeerReviewed |2 local | |
| 787 | 0 | |n https://ir.uitm.edu.my/id/eprint/54359/ | |
| 856 | 4 | 1 | |u https://ir.uitm.edu.my/id/eprint/54359/ |z Link Metadata |