Game data collection system is a tool used to collect the behavior data of users about the game. It can be used for data analysis of user behavior so that game manufacturers can keep abreast of market dynamics and popular trends, and they also can have a deeper understanding of the behavioral habits and psychology of player user groups. The defects of the current data acquisition system include that the data are not encrypted. The network transmission efficiency is relatively low. The acquisition speed is slow, and the settings cannot be dynamically changed. This paper proposes to study how to enhance the acquisition ability and improve the analysis efficiency in the design of data acquisition system for solving these problems. Therefore, on the basis of artificial intelligence algorithm, this paper designs a game data collection system by using artificial neural network algorithm, support vector algorithm, and cluster analysis algorithm, which solves the basic problem of slow data collection in current data collection and plays a role in improving the efficiency of network transmission. The experimental results in this paper show that when the number of data is more than 300, the time-consuming time reaches more than 68 ms. When the number of written data is more than 300, it takes more than 181 ms. When the number of deleted data is more than 300, it takes more than 236 ms. From the above data, it shows that the designed game data collection system is rapid and efficient.
机构:
Zhejiang Fash Inst Technol, Business Sch, Ningbo 315000, Zhejiang, Peoples R ChinaZhejiang Fash Inst Technol, Business Sch, Ningbo 315000, Zhejiang, Peoples R China
机构:
Yulin Univ, Sch Energy Engn, Yulin 719100, Shaanxi, Peoples R China
Yulin Univ, Lab Coherent Raman Scattering, Yulin 719000, Shaanxi, Peoples R ChinaYulin Univ, Sch Energy Engn, Yulin 719100, Shaanxi, Peoples R China
Yang, Ting
Qian, Xiyang
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机构:
Yangzhou Univ, Coll Elect Energy & Power Engn, Yangzhou 225127, Jiangsu, Peoples R ChinaYulin Univ, Sch Energy Engn, Yulin 719100, Shaanxi, Peoples R China
Qian, Xiyang
Ren, Liqing
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机构:
Yulin Univ, Sch Energy Engn, Yulin 719100, Shaanxi, Peoples R China
Yulin Univ, Lab Coherent Raman Scattering, Yulin 719000, Shaanxi, Peoples R ChinaYulin Univ, Sch Energy Engn, Yulin 719100, Shaanxi, Peoples R China
Ren, Liqing
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS,
2022,
2022
机构:
Hanseo Univ, Dept Convergence Design, Seosan 31962, Chungcheongnam, South KoreaHanseo Univ, Dept Convergence Design, Seosan 31962, Chungcheongnam, South Korea
Rong, Jinjin
Ji, Xu
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机构:
Anhui Univ Finance & Econ, Sch Art, Bengbu 233000, Anhui, Peoples R ChinaHanseo Univ, Dept Convergence Design, Seosan 31962, Chungcheongnam, South Korea
Ji, Xu
Fang, Xin
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机构:
Anhui Normal Univ, Coll Fine Arts, Wuhu 241002, Anhui, Peoples R ChinaHanseo Univ, Dept Convergence Design, Seosan 31962, Chungcheongnam, South Korea
Fang, Xin
Jee, Moon-Hwan
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机构:
Hanseo Univ, Dept Convergence Design, Seosan 31962, Chungcheongnam, South KoreaHanseo Univ, Dept Convergence Design, Seosan 31962, Chungcheongnam, South Korea