Game Flow Recognition Based on BP Neural Network and Optimized Genetic Algorithm

• 발행기관: 한국컴퓨터게임학회
• 저자명: Daniel James
• 간행물 정보: 『한국컴퓨터게임학회논문지』제34권 3호, 99~108쪽, 전체 10쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2021.09.30

영문 초록

As a new entertainment and social way, online games now have a huge and increasing user group, so it is of great significance to identify the data stream of online games. Using the excellent nonlinear fitting ability of BP neural network and the advantages of global search of genetic algorithm, the initial weights and thresholds of BP neural network are optimized, and the BP neural network model optimized by genetic algorithm is established. The muti-dimensional input information is proposed to identify online game data streams. Through the experimental simulation, it shows that the selected muti-dimensional information and the established model can be well applied to online game stream recognition.

목차

1. Introduction

2. BP neural network optimized by genetic algorithm

3. Network game data stream recognition model

4. Experimental analysis

6. Conclusions

키워드

BP neural network Genetic algorithm Game stream recognition Muti-dimensional information