自己紹介・研究目的
令和4年度入学/ ■SPRING事業 採択学生紹介
数理・ヒューマンシステム科学専攻
令和4年度 大学院入学
王 愷昱
オウ ガイイク
Related research and application of evolutionary algorithms
Hello, everyone! My name is Kaiyu Wang, I am a doctor student in University of Toyama, Graduate School of Science and Engineering, Advanced Mathematics and Human Mechanisms, Artificial Intelligence lab. I am now researching on computational intelligence and neural networks for real-world applications.
In the present society, there are many complex optimization problems to be solved. Evolutionary algorithms (EAs) are an important branch of artificial intelligence and an excellent way to solve these problems, so it becomes important to continuously improve the performance of the algorithms. During my master's degree, I proposed an algorithm and used it for the solar parameter estimation problem and was the champion on this problem at that time. In my PhD, I will continue my research and try to propose the best performing algorithm on single objective optimization problems and also use it in various real world problems in industry.
I will try to consider adaptive variation of two important parameters in the FO population. EA with FO population currently does not perform well on the single-objective optimization problems. It is Important to apply the adaptive FO population to the current champion algorithm for single-objective optimization problems and outperform the champion algorithm in terms of performance.(旧フェローシップ事業採択学生)
In the present society, there are many complex optimization problems to be solved. Evolutionary algorithms (EAs) are an important branch of artificial intelligence and an excellent way to solve these problems, so it becomes important to continuously improve the performance of the algorithms. During my master's degree, I proposed an algorithm and used it for the solar parameter estimation problem and was the champion on this problem at that time. In my PhD, I will continue my research and try to propose the best performing algorithm on single objective optimization problems and also use it in various real world problems in industry.
I will try to consider adaptive variation of two important parameters in the FO population. EA with FO population currently does not perform well on the single-objective optimization problems. It is Important to apply the adaptive FO population to the current champion algorithm for single-objective optimization problems and outperform the champion algorithm in terms of performance.(旧フェローシップ事業採択学生)