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首页> 外文期刊>Journal of Computers >The Accuracy Rate of Holt-Winters Model with Particle Swarm Optimization in Forecasting Exchange Rates
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The Accuracy Rate of Holt-Winters Model with Particle Swarm Optimization in Forecasting Exchange Rates

机译：预测汇率中粒子群优化的Holt-Winters模型的精度率

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—Exchange rates forecasting is a crucial and challenging task. Accurate forecasting of the imminent movements of exchange rates is very important in investments, trade and economics. In this paper, an exponential smoothing using the Holt-Winters Model is used for forecasting exchange rates. Parameter search for the smoothing constants is done through computer simulation using Particle Swarm Optimization (PSO). Experiment results show that PSO is able to compute good values for the smoothing constants, producing forecasts with accuracy in determining the direction (rise or fall) of exchange rates. Furthermore, the computed Mean Absolute Deviation (MAD) and the Residual Standard Error (RSE) of the exchange rate forecasts from the actual observed data indicate that PSO can also be used to improve forecasting precision.
机译：-Exchange费率预测是一个至关重要的，具有挑战性的任务。准确的预测即将发生的汇率转移在投资，贸易和经济方面非常重要。在本文中，使用Holt-Winters模型的指数平滑用于预测汇率。参数搜索平滑常量是通过使用粒子群优化（PSO）的计算机仿真完成的。实验结果表明，PSO能够计算平滑常数的良好值，在确定汇率的方向（上升或下降）时，生产预测。此外，从实际观察数据的汇率预测的计算平均绝对偏差（MAD）和残余标准误差（RSE）表明PSO也可用于提高预测精度。

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