Player Game Flow Data Analysis And Modeling

In recent years,due to the increasing attention to the game industry,the status of the game industry in life has gradually improved,more and more people have higher requirements for all aspects of the game.However,the traditional way can not get the real-time physiological and psychological situation of the players in the process of the game,so it is unable to make a detailed quantitative analysis and evaluation for specific links in the follow-up.In view of this application scenario,this paper studies and designs a set of analysis and modeling framework,which improves some evaluation methods in this field.Based on the concept of game flow,this paper makes prediction and classification of players' situation in the process of game based on game data.In this paper,from the perspective of framework introduction,according to the overall framework process,all the methods and algorithms used are introduced in detail,and all the results are displayed and explained.The work of this paper is to build a set of scientific player body and mind data collection equipment and platform from multi-dimensional data,through which we can get multi-dimensional game data and player body and mind data.After multi-dimensional data collection,through the sliding window based deep learning optimal correlation sequence analysis DTW matching algorithm,the time series of players' emotions and game flow are obtained.Finally,the accuracy and reliability of these sequences are verified,and the siamese network and the personality embedding is used to classify and predict the game flow,so as to get the strength of the game flow directly from the game data.This paper focuses on the design and modeling of the whole model framework,a set of DTW matching algorithm based on sliding window for deep learning optimal correlation sequence analysis and game flow classification and prediction algorithm.Through the above methods,a more reliable player flow data analysis and modeling tool is obtained,which can be effectively applied to the analysis and modeling of player flow and the analysis and improvement of the game.