ターケンスの埋め込み定理を組み込んだニューラルネットワークの BP法を用いたテストスコアの短期予測

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At the fifty-first national conference of the Japan Association for Language Education and Technology (LET), we reported the possibility of using a neural network to make short-term predictions of language test scores if they are in a chaotic time-series. At that time, one possible area for further development was increasing the accuracy of the prediction. In our presentation, we will discuss the utility of improving accuracy by applying Takens’ theorem to the short-term chaotic time-series prediction using the well-known Backpropagation Method.

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