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Group Method of Data Handling with Artificial Bee Colony in Combining Forecasts

机译:组合预测中人工蜂群数据处理的分组方法

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In this study, the use of Artificial Intelligence (AI) algorithm to combine several time series forecasts is presented. This study is done by combining individual forecasts of Group Method of Data Handling models using the weighted-based combine approach. The weights for each individual model are calculated using Artificial Bee Colony algorithm. In order to evaluate the proposed model, this study tested the proposed model on the International Airline Passengers data, and the performances are calculated using mean square error (MSE), mean average error (MAE) and mean average percentage error (MAPE). The accuracy of the proposed model is compared to the individual models and the models implemented in previous literatures. The results revealed that the proposed model is able to produce significantly accurate forecasts.
机译:在这项研究中,提出了使用人工智能(AI)算法来组合多个时间序列预测的方法。这项研究是通过使用基于加权的合并方法合并数据处理模型的分组方法的各个预测来完成的。使用人工蜂群算法计算每个模型的权重。为了评估提出的模型,本研究在国际航空公司的乘客数据上测试了提出的模型,并使用均方误差(MSE),平均平均误差(MAE)和平均平均百分比误差(MAPE)计算了性能。将所提出的模型的准确性与单个模型和先前文献中实现的模型进行比较。结果表明,所提出的模型能够产生非常准确的预测。

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