Title page for etd-0624123-154215

URN	etd-0624123-154215	Statistics	This thesis had been viewed 94 times. Download 12 times.
Author	Chun Ha n Chen
Author's Email Address	packerek76@gmail.com
Department	Institute of Industrial Management
Year	2022	Semester	2
Degree	Master	Type of Document	Master's Thesis
Language	zh-TW.Big5 Chinese	Page Count	50
Title	Using A rtificial Intelligence Methods to Explore the Prediction o f American Professional Baseball Games
Keyword	accuracy. model optimization neura l network win loss prediction Professional baseball games Professional baseball games win loss prediction neura l network model optimization accuracy.
Abstract	Professional baseball game prediction has always been a popular research topic in the industry/academia. In addition to the high prize money, the prediction difficulty is also very high. There are many studies in the literature using various formal or informal methods to obtain many interesting results, but these results are difficult to apply to future sports event prediction. This study attempts to use the current popular artificia lintelligence method neural network, applied to the prediction of American professional baseball games, and obtained the characteristics and results of the best neural network model. These unexpected results can be an important reference for researchers who are also engaged in this field. This study uses the historical data of the American Giants and Dodgers games as an example to illustrate how to apply this model for prediction of games.
Advisor Committee	Shin-Guang Chen - advisor Cheng-Ta Yeh - co-chair Ping-Chen Chang - co-chair
Files	etd-0624123-154215.pdf indicate access worldwide
Date of Defense	2023-06-09	Date of Submission	2023-06-24

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