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The Case Study of Adaptive Network-Based Fuzzy Inference System Modeling for TAIEX Prediction

机译:基于自适应网络的模糊推理系统建模的Taiex预测的案例研究

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The purpose of this research is to investigate the relation between international stock markets and Taiwan's stock market, and use the statistical method to identify international markets of high correlation with Taiwan's stock market as the input parameters of the ANFIS (Adaptive Network-based Fuzzy Inference System) model to improve the forecasting accuracy. This paper collects dataset in the period of years 2000~2010 from 13 countries including Japan, Singapore, Malaysia of high correlation with Taiwan. to prove the forecasting effectiveness of the model, this paper compares the proposed model with models proposed in other studies. the experimental results suggest that, the total average RMSE of the proposed model is lower as compared with other models. the contribution of this research is to integrate the statistical method and ANFIS model to effectively enhance the forecasting accuracy for TAIEX stock price prediction.
机译:本研究的目的是调查国际股市与台湾股市之间的关系,并利用统计方法确定与台湾股市高相关的国际市场作为ANFIS的输入参数(基于自适应网络的模糊推理系统 )模型提高预测精度。 本文从包括日本,新加坡,马来西亚与台湾高度相关的13个国家/ 2010年收集数据集。 为了证明模型的预测效果,本文将提出的模型与其他研究提出的模型进行了比较。 实验结果表明,与其他模型相比,所提出的模型的总平均RMSE较低。 本研究的贡献是整合统计方法和ANFI模型,以有效提高TAIEX股价预测的预测精度。

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