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1 June 2023 Data mining and prediction based on Wordle
Xiang Zhao, Tianqi Hao, Zhe Ren
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Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127182B (2023) https://doi.org/10.1117/12.2681578
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China
Abstract
For the wordle game, we mainly want to determine whether its daily words have an impact on the proportion of people participating in the difficult mode. We need to predict the distribution of the number of attempts in the future difficult mode, so we can use neural network to establish the MIMO(Multiple-Input-Multiple-Output) BP neural network model. This model encodes words as input. We set the transformation function of the model as tansig and purelin, the integration function as trainlm, and the learning function as learngdm. Then we set the number of training to 1000, and the mean square error of training is 0.005. After that, we can train the model and draw a conclusion.
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Xiang Zhao, Tianqi Hao, and Zhe Ren "Data mining and prediction based on Wordle", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127182B (1 June 2023); https://doi.org/10.1117/12.2681578
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KEYWORDS
Education and training
Data modeling
Neural networks
Data mining
Signal processing
MATLAB
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