Decision Tree Based Decision Optimization Algorithm for Yangqin Performance
Lin Wei-Lun · 2022
As a traditional folk music, the yangqin has a large gap in the extraction of performance style and features compared with western instruments, and the existing decision making of the yangqin played by a robotic arm has relatively low utilization of the instrument surface. To address this research gap, this paper develops a decision tree based decision optimization algorithm for yangqin performance, which obtains the subsequent assignment results from the previous assignment results, the relative position of the central axis of the instrument surface, and other parameters. This paper illustrates the feasibility of this method from the principle, and designs several sets of controlled experiments to demonstrate that this method can effectively reduce the load of the robotic arm system, increase the utilization range of the instrument surface, and make the allocation results more similar to human habits.