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003 KUKTEM
005 20251117113226.0
008 141014t2013 my da f m 000 0 eng d
020 _aTHE0007285(Local)
039 9 _a201905141147
_bfawwaz
_c201411051216
_dsafura
_y201410141027
_zFida
040 _aUMP
090 _aTL257 .L87 2013 r Bc.
100 0 _aMohamad Luqman Zaki Monsarif
245 1 0 _aModeling magneto-rheological damper using neural network and simulated annealing /
_cMohamad Luqman Zaki Monsarif
260 _aKuantan, Pahang :
_bUMP,
_c2013
300 _axiii, 53 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD-ROM
502 _aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2013
504 _aBibliography : p. 52-53
520 3 _aThis thesis is study about modeling the Magneto-rheological damper using Neural Network and Simulated Annealing method. Five different values of current were used in order to modeling the MR damper, which are 0.0 ampere, 0.5 ampere, 1.0 ampere, 1.5 ampere and 2.0 ampere. In order to modeling the MR damper, the graph of simulation damper will be compared with the experimental damper. The results will get the Square Error for the simulation damper. Then, the Root Mean Square Error will be calculated to get the difference between the simulation damper and experimental damper. The results show that the lowest RMSE for the simulation damper were value 1.282457, while the highest RMSE is 13.18909. From the results also, the better current value to modeling the MR damper is using the MR damper with the lowest RMSE.
650 0 _aAutomobiles
_xSprings and suspension
_xDesign and construction
650 0 _aDamping (Mechanics)
999 _aVIRTUA40
_c5005
_d5011
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992