Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 149-151.

• Intelligent Computing • Previous Articles     Next Articles

Tactical Analysis of MOBA Games Based on Hotspot Map of Battlefield

YU Cheng1, ZHU Wan-ning1,2   

  1. Department of Software Engineering,Jinling Institute of Technology,Nanjing 211169,China1
    Department of Computer Science and Engineering,Southeast University,Nanjing 211189,China2
  • Online:2019-02-26 Published:2019-02-26

Abstract: With the continuous development of the e-sports industry,except for the decisive factors such as experience,talent and skills,data analysis has an increasing influence on the winners and losers of MOBA games.For the problem that some MOBA games are unable to obtain accurate data directly through the interface,this paper proposed a method that gives pretreatment for position data according to the official heat maps and used PNN (Probabilistic Nearest Neighbor) with the idea of prototype clustering for tactical analysis.Finally,tactics is derived in the form of a probability:mobile probability for core characteristics of sides to core of the battle.In this algorithm,weighted distance is added to improve KNN’s shortcoming of using Euclidean distance to calculate the difference between sample points,and the least square method is used to obtain the optimal constant solution.At the same time,all distance data are normalized to improve the accuracy of the algorithm.The final experiment shows that this method is effective in predicting the probability of the core point of the battlefield.

Key words: E-sports, Least square method, MOBA tactical analysis, PNN algorithm, Weighted distance

CLC Number: 

  • TP391
[1]何培奕.中国电子竞技产业的现状和发展研究[D].上海:上海外国语大学,2013.
[2]张锐.中国电子竞技进入最好的时代[N].证券时报,2017-10-10(A03).
[3]任一彬.中国电竞英雄联盟中国队S5季中赛制胜因素分析[D].西北师范大学,2016.
[4]田绍兴,陈劲杰.基于KNN的手写数字的识别[J/OL].农业装备与车辆工程,2017(10):96-97,100.http://kns.cnki.net/kcms/detail/37.1433.TH.20171024.0703.044.html.
[5]SEBASTIANI F.Machine learning in automated text catagori-zaition [J].ACM Computing Surveys,2002,31(2):1-17.
[6]李航.统计学习方法 [M].北京:清华大学出版社,2012:37-45.
[7]丁克良,沈云中,欧吉坤.整体最小二乘法直线拟合[J].辽宁工程技术大学学报(自然科学版),2010,29(1):44-47.
[8]ALISON J,DUFFIELD S J,MORECROFT M D,et al.Successful restoration of moth abundance and species-richness in grassland created under agri-environment schemes[J].Biological Conservation,2017,213:51-58.
[9]KIM J,HONG T,JEONG J,et al.An integrated psychological response score of the occupants based on their activities and the indoor environmental quality condition changes[J].Building and Environment,2017,123:66-77.
[10]DECUYPER J,DE TROYER T,RUNACRES M C,et al.Nonlinear state-space modelling of the kinematics of an oscillating circular cylinder in a fluid flow[J].Mechanical Systems and Signal Processing,2018,98:209-230.
[11]LIN Z Y,ZHANG L X.Convergence to a self-normalized G-Brownian motion[J].Probability,Uncertainty and Quantitative Risk,2017,2(1):4.
[1] TANG Jia-lin, ZHANG Chong, GUO Yan-feng, SU Bing-hua and SU Qing-lang. Color Difference Correction Algorithm Based on Multi Colors Space Information [J]. Computer Science, 2020, 47(6A): 157-160.
[2] SONG Rui-yang, MENG Hua, LONG Zhi-guo. Linear Twin Support Vector Machine Based on Data Distribution Characteristics [J]. Computer Science, 2019, 46(6A): 407-411.
[3] LENG Ya-hong. Optimization Method of Support Domain Radius of Moving Least Squares Agent Model [J]. Computer Science, 2016, 43(Z6): 95-98.
[4] XIONG Zhe, JIA Jie and CHEN Jian. Distributed Localization Scheme Based on Virtual Force in Wireless Sensor Networks [J]. Computer Science, 2016, 43(2): 109-112.
[5] . Incremental SVM Intrusion Detection Algorithm Based on Distance Weighted Template Reduction and Attribute Information Entropyc [J]. Computer Science, 2012, 39(12): 76-78.
[6] . [J]. Computer Science, 2006, 33(2): 166-168.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!