Nur Nafara Rofiq, . (2015) Implementasi Fuzzy Inference System Metode Mamdani Pada Automatic Vehicle Classification (AVC) System (Hasil Penelitian Dosen UNPAM, 2015 ). Universitas Pamulang, Tangerang Selatan.
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Abstract
Classification of vehicle's type is critical in determining the class of vehicles passing on the highway. It is closely related to the rate payable on toll transaction system for the vehicle. Misclassification often occurs due to the similarity Bus vehicle body shape and medium size trucks (Truck Box 3/4), therefore it takes an expert system to determine the classification of vehicles on the Automatic Vehicle Classification (AVC) System. The concept of fuzzy logic easy to understand, mathematical concepts behind fuzzy reasoning is simple and fuzzy logic can work with conventional control system. This research used fuzzy inference system with Mamdani method to find solutions to existing problems. The length of the vehicle body flatness and long wheelbase Axle as variable input, while the output variable is the class of the vehicle. The test results in this study achieved the value of accuracy 86.7%. Keywords: Classification, Automatic Vehicle Classification (AVC) System, fuzzy inference system, accuracy Nur Nafara Rofiq, Implementation of Fuzzy Inference System Mamdani Method On Automatic Vehicle Classification (AVC) System. Universitas Pamulang, South Tangerang 61 + vii pages / 15 tables / 43 pictures / 25 references (1997-2012)
| Item Type: | Other |
|---|---|
| Subjects: | Q Science > Q Science (General) |
| Depositing User: | Admin Perpustakaan UNPAM |
| Date Deposited: | 13 Nov 2015 06:57 |
| Last Modified: | 13 Nov 2015 06:57 |
| URI: | http://repository.unpam.ac.id/id/eprint/732 |
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