ABSTRACT Including uncertainties such as the performance of the teams, player performance indicators, and the quality of the competitors, there are numerous factors affecting the result of a game. Therefore, prediction of the game results is quite a complicated and a conspicuous research problem. Various artificial intelligence models were developed in order to solve this problem. By drawing together the advantageous sides of various artificial methods, this study aims to develop a hybrid intelligent system in order to better predict the result of a basketball game. Firstly, a prediction model was developed via artificial neural network (ANN), which is frequently used in game result predictions. The success of this developed ANN model in predicting the result of the game was 70.8%. In order to increase this success rate, a new concurrent neuro fuzzy system (CNFS) was suggested which was combined with fuzzy logic system that determined whether the team was favorite. The accurate prediction rate increased to 79.2% via this suggested CNFS model. Moreover, the results of the models developed were compared with each other and previous studies predicting the game results. As the conclusion of the comparisons, it was observed that CNFS model had a remarkable talent in predicting the game results.

中文翻译：

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一种使用并发神经模糊系统的新型篮球结果预测模型

摘要 包括球队表现、球员表现指标、选手素质等不确定因素，影响比赛结果的因素很多。因此，博弈结果的预测是一个相当复杂且引人注目的研究问题。为了解决这个问题，开发了各种人工智能模型。本研究综合各种人工方法的优点，旨在开发一种混合智能系统，以更好地预测篮球比赛的结果。首先，通过人工神经网络（ANN）开发了预测模型，该模型经常用于游戏结果预测。这种开发的 ANN 模型在预测比赛结果方面的成功率为 70.8%。为了提高这个成功率，提出了一种新的并发神经模糊系统（CNFS），该系统与模糊逻辑系统相结合，以确定团队是否受欢迎。通过这个建议的 CNFS 模型，准确预测率增加到 79.2%。此外，将开发的模型的结果相互比较，并与之前预测游戏结果的研究进行比较。作为比较的结论，可以看出 CNFS 模型在预测比赛结果方面具有非凡的才能。