Global optimization and simulated annealing
Mathematical Programming: Series A and B
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The nature of statistical learning theory
The nature of statistical learning theory
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Forecasting stock market movement direction with support vector machine
Computers and Operations Research
Software reliability forecasting by support vector machines with simulated annealing algorithms
Journal of Systems and Software
Dynamic support vector machines for non-stationary time series forecasting
Intelligent Data Analysis
Space-time modeling of traffic flow
Computers & Geosciences
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Due to complex nonlinear data pattern in time series regression, forecasting techniques had been categorized in different ways, and the literature is also full of differing opinions, thus, it is difficult to make a general conclusion. In the recent years, the support vector regression (SVR) model has been widely used to solve nonlinear time series regression problems. This investigation presents a short-term traffic forecasting model by employing SVR with genetic algorithm and simulated annealing algorithm (GA-SA) to determine the suitable parameter combination in the SVR model. Consequently, a numerical example of traffic flow values from northern Taiwan is used to demonstrate the forecasting performance of the proposed SVRGA-SA model is superior to the seasonal autoregressive integrated moving average (SARIMA) time series model.