Prediction of Wordle player data based on BP neural network optimized by genetic algorithm

Abstract

This article mainly uses the data provided by Wordle player to predict the distribution of score results for a certain word in the future. However, the scoring results have high uncertainty. There are many evaluation indicators and impact factors. In order to predict the results more accurately, this paper proposes a BP neural network data prediction model based on genetic algorithm optimization(GA BP algorithm). We introduce three factors: time, prevalence of each word and number of repeated letters. We determine the BP neural network topology, each parameter of BP and each parameter of GA, then train it. The data correlation between the training set, validation set, test set and overall results after training is derived and the result is good. The predicted result for the term EERIE on March 1, 2023 is: 0.00%, 2.06%, 16.21%, 32.95%, 28.50%, 15.78%, 4.48% from 1 to X in that order.