000			01806ntm a2200253 a 4500
001			vtls000083707
003			KUKTEM
005			20251117113249.0
008			141119t2013 my a f m 000 0 eng d
020			_aTHE0007280(Local)
039		9	_a201905141144 _bfawwaz _y201411191601 _zfawwaz
040			_aUMP
090			_aTL257 .F55 2013 r Bc.
100	0		_aMohd Fikri Arifin
245	1	0	_aModelling magneto-rheological damper using radial basis function neural network / _cMohd Fikri Arifin
260			_aKuantan, Pahang : _bUMP, _c2013
300			_axvii, 48 p. : _bill. ; _c30 cm. + _e1 CD-ROM
502			_aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2013
504			_aBibliography : p. 48
520	3		_aThis a study on modeling the MR damper using RBF. MR damper can be simplify as a damper that using MR fluids. MR fluid contains magnetic particles which will react to current flow when power is supplied. The viscosity of the fluid depends on the current flow. The stiffness of the damper depends on the fluids. This modeling is to achieve the similarity of the results of the experiment using proper machine and apparatus and by using MATLAB software. The data that are obtained from the experiment are used in the MATLAB software to generate graphs. The RBF equations are used in the m-file to get the similarity as the graph from experiment. Comparisons between the graphs are decided by inspection and the most accurate, by using the RMSE graph. The input in m-file is adjusted again and again to get the smallest RMSE as possible
650		0	_aAutomobiles _xSprings and suspension _xDesign and construction
650		0	_aDamping (Mechanics)
999			_aVIRTUA40 _c5724 _d5730
999			_aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992