01747ntm a2200241 a 4500 vtls000072062 KUKTEM 20251114204536.0 130617t2012 my da f m 000 0 eng d THE0007373(Local) 201905151047 fawwaz 201306171453 huda 201306171445 huda UMP TL574.S7 A35 2012 rs Bc. Muhammad Afiq Naquiddin Abd Rahman Modeling the magneto- rheological damper using recurrent neural network method / Muhammad Afiq Naquiddin Abd Rahman Kuantan, Pahang : UMP, 2012 xiv, 47 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2012 Bibliography : p. 46-47 This thesis is study about modeling the Magnetorheological damper using Recurrent Neural Network 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 0.4008, while the highest RMSE is 1.9882. From the results also, the better current value to modeling the MR damper is using the MR damper with the lowest RMSE. Damping (Mechanics) 0 0 0 1 20000 20000 2019-09-04 0 TL574.S7 A35 2012 rs Bc. 0000069762 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 20000 20000 2019-09-04 0 CD 6632 | TL574.S7 A35 2012 rs Bc. 0000069763 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 3844 3850 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992