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In this research, hybrid model of Least Square Support Vector Machine (LSSVM) and Ensemble Empirical Mode Decomposition (EEMD) are presented to forecast tourism demand in Malaysia. Foremost, the original series of tourism arrivals data was separated using EEMD technique into residual and Intrinsic Mode Functions (IMFs) components. Next, both of IMFs and residual components were forecasted using Particle Swarm Optimization (LSSVM-PSO) method. In the end, the predicted result of IMFs and residualdoi:10.17485/ijst/2016/v9i36/97773 fatcat:pwdtbvmkonhpla2zh7vbpleio4