Запис Детальніше

MATCHES PROGNOSTICATION FEATURES AND PERSPECTIVES IN CYBERSPORT

Науковий журнал «Радіоелектроніка, інформатика, управління»

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Поле Співвідношення
 
##plugins.schemas.marc.fields.042.name## dc
 
##plugins.schemas.marc.fields.245.name## MATCHES PROGNOSTICATION FEATURES AND PERSPECTIVES IN CYBERSPORT
 
##plugins.schemas.marc.fields.720.name## Korobchynskyi, M. V.; Military-Diplomatic Academy named by Eugene Bereznyak, Kyiv
Chyrun, L. B.; Lviv Polytechnic National University
Vysotska, V. A.; Lviv Polytechnic National University
Nych, M. O.; Lviv Polytechnic National University
 
##plugins.schemas.marc.fields.653.name## Сybersport; prediction; information system.
 
##plugins.schemas.marc.fields.520.name## <p>Context. The forecasting system fixing in cybersport is relevant at this point, it is connected to an active development cybersport. In this paper the ability to predict matches users is implemented.</p><p>Objective. The purpose of this work is the system model design of collective predicting outcomes of games results in cyber sport using modern technology of the neuro forecasting. The task is a system development for common user forecasting results of matches cybersport and independent information processing and issuing its own forecast. The main tasks include: all past and future games accounting and analysis; all teams performance / results accounting and analysis; user capabilities to make personal prediction for every match; determining the team winning odds based on previous matches.</p><p>Method. The problem by the survey of experts by means of analytical reports and using artificial neural network is solved. ANN is established in three layers. The first layer consists of 10 neurons-receptors, neurons of inputs data. The second layer of neurons is inside. The third layer is the source of neurons, it is only 2 neurons. The input data for the algorithm is the number of matches won the last 10; the number of won games before this meeting; team rating; stability of (time invariance of the team); the average of the losing team. The answer is 1 or 2 (the victory of a particular team).</p><p>Results. To achieve the cops of the relevant literature with information about the main types of collective prediction is reviewed. A tree objectives, and conducted a systematic analysis of the future system is developed. In this paper the method of interviews with experts and implemented it in their system is altered. Online resources implemented with CMS Drupal. The basic methods of collective prediction are described. A systematic analysis of the research object and subject is developed; objectives tree is developed and the problem and constructed UML-diagrams are studied. The method of interviews with experts and the use of this method in the paper are described. The implementation of a web site with CMS Drupal and programming language PHP is showed.</p><p>Conclusions. Based on the algorithm calculation example and training artificial neural network independent of the human factor in the process of predicting matches cyber sport is implemented. The presence of such system greatly simplifies the search for example cyber sports matches and give everyone the opportunity to take part in predicting matches. This system can give new impetus to the problem of predicting results not only in cyber-sport and sport in general.</p>
 
##plugins.schemas.marc.fields.260.name## Zaporizhzhya National Technical University
2017-11-30 09:44:40
 
##plugins.schemas.marc.fields.856.name## application/pdf
http://ric.zntu.edu.ua/article/view/115504
 
##plugins.schemas.marc.fields.786.name## Radio Electronics, Computer Science, Control; No 3 (2017): Radio Electronics, Computer Science, Control
 
##plugins.schemas.marc.fields.546.name## uk
 
##plugins.schemas.marc.fields.540.name## Copyright (c) 2017 M. V. Korobchynskyi, L. B. Chyrun, V. A. Vysotska, M. O. Nych