Prediction of Wordle player data based on ARIMA time series model

Jiaqi Liu; Decong Chen; Yang Ma; Jinpeng Cheng; Lanbo Xu

doi:10.1117/12.2686270

28 July 2023 Prediction of Wordle player data based on ARIMA time series model

Jiaqi Liu, Decong Chen, Yang Ma, Jinpeng Cheng, Lanbo Xu

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 127563N (2023) https://doi.org/10.1117/12.2686270
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

This paper focuses on predicting the results of wordle players' data. Firstly, the data is preprocessed according to the provided data, the ARIMA time series model is constructed, the ADF test is conducted, and then the correlation coefficient is obtained for model verification. The overall analysis of the model is made to determine that the model meets the requirements, and the future time results are predicted. Then, another fitting algorithm model is constructed, and the optimal function model is found through many attempts, its related parameters are calculated, its fitting effect is determined, and the subsequent results are predicted. Finally, we take the prediction results of the two models as the threshold of the prediction interval, and the result is [10860,18524].

Citation Download Citation

Jiaqi Liu, Decong Chen, Yang Ma, Jinpeng Cheng, and Lanbo Xu "Prediction of Wordle player data based on ARIMA time series model", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 127563N (28 July 2023); https://doi.org/10.1117/12.2686270

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