Bicycle Frame Prediction Techniques with Fuzzy Logic Method

Authors

  • Rafiuddin Syam Hasanuddin University

Keywords:

Bicycle, height, inseam, Crank Size, frame size, fuzzy logic

Abstract

In general, an appropriate size bike frame would get comfort to the rider while biking. This study aims to predict the simulation system on the bike frame sizes with fuzzy logic. Testing method used is the simulation test. In this study, fuzzy logic will be simulated using Matlab language to test their performance. Mamdani fuzzy logic using 3 variables and 1 output variable intake. Triangle function for the input and output. The controller is designed in the type mamdani with max min composition and the method deffuzification using center of gravity method. The results showed that height, inseam and Crank Size generating appropriate frame size for the rider associated with comfort. Has a height range between 142 cm and 201 cm. Inseam has a range between 64 cm and 97 cm. Crank has a size range between 175 mm and 180 mm. The simulation results have a range of frame sizes between 13 inches and 22 inches. By using the fuzzy logic can be predicted the size frame of bicycle suitable for the biker

References

[1] Pusparini, Putu, “Pengaruh Sudut STA Angka Sepeda Terhadap Nilai Risiko Cedera Tubuh Pengendara Sepeda”, Tugas Akhir Mahasiswa Jurusan Teknik Mesin, FTI-ITS, 2009

[2] Tedja, Andra Berlianto, “Analisa Tegangan dan Deformed Shape Pada Rangka Sepeda Fixie”, Tugas Akhir Mahasiswa Jurusan Teknik Mesin, FTI-ITS, 2012

[3] A. Zadeh, Lutfi, “Fuzzy Logic”, University of California, Berkeley

[4] Argawal, Manish, “Fuzzy Logic Control of Washing Machines”, Indian Institute of Technology, unpublished

[5] Kusumadewi, Sri dan Hari Purnomo, “Aplikasi Logika Fuzzy untuk Pendukung Keputusan”, Graha Ilmu, 2010

[6] Widodo, Prabowo Pudjo dan Rahmadya Trias Handayanto, “Penerapan Soft Computering Dengan MATLAB”, Rekayasa

Sains, Bandung, 2012(in Bahasa)

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Published

2015-04-10

How to Cite

[1]
R. Syam, “Bicycle Frame Prediction Techniques with Fuzzy Logic Method”, IJSMM, vol. 2, no. 1, pp. 34–41, Apr. 2015.