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Strategies for analyzing the guessing game "Wordle"

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DOI: 10.23977/jeis.2023.080601 | Downloads: 9 | Views: 197


Peixin Guo 1, Baoqi Wang 2, Zuyou Fan 2


1 College of Transportation Engineering, Chang'an University, Xi'an, Shaanxi, 710061, China
2 School of Energy and Electrical Engineering, Chang'an University, Xi'an, Shaanxi, 710061, China

Corresponding Author

Peixin Guo


Nowadays, games have become indispensable for people's entertainment. Among them, the five-letter decryption game "world" launched by the New York Times has swept the world. Many players also reported their scores on Twitter. Through these published data, we found some interesting information. According to the information and requirements given by the topic, the table data attached to the topic is preprocessed. Find an exception in the data and delete it. The attributes of a given word are extracted by data encoding. We draw a line graph of the data, observe its trend change and perform curve fitting. The study found that the first half of the curve rose rapidly and the second half fell slowly. The fitting curve function was obtained, and the goodness of fit were 0.9521 and 0.9629, respectively. Using the curve, the quantitative range of results reported on March 1, 2023 is [5805.390,6075.43]. The sensitivity analysis was carried out by changing the four parameters of the fitting curve. The results show that the predicted value is within the reasonable range. Based on the parts of speech classification and the number of letter repeats, we investigate whether they affect the percentage distribution of difficult sentence patterns. Secondly, we optimize the LSTM model based on particle swarm optimization algorithm, and carry out hyperparameter optimization processing to build the PSO-LSTM model. Compared with LSTM, it is found that its model expression is better than that of single LSTM model. The MAPE value of the test set is 1.248, which means the uncertainty is 1.248%, so we have 98.752 percent confidence in the accuracy of the model. The EERIE data were encoded and put into the established PSO-LSTM model, and the correlation percentages were 0.432, 3.631, 19.326, 30.291, 26.954, 14.234 and 5.132, respectively.


Wordle; Curve Fitting; PSO-LSTM


Peixin Guo, Baoqi Wang, Zuyou Fan, Strategies for analyzing the guessing game "Wordle". Journal of Electronics and Information Science (2023) Vol. 8: 1-6. DOI:


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