Artificial Neural Network를 이용한 화살 성능에 대한 연구

Abstract

In order to evaluate the performance of arrow that manufactures through production process, it is used that personal experiences such as hunters who have been using bow and arrow for a long time, technicians who produces leisure and sports equipment, and experts related with this industries. Also, the intensity of arrow`s impact point which obtains from repeated shooting experiments is an important indicator for evaluating the performance of arrow. There are some ongoing researches for evaluating performance of arrow using intensity of the arrow`s impact point and the arrow`s flying image that obtained from high-speed camera. However, the research that deals with mutual relation between distribution of the arrow`s impact point and characteristics of the arrow (length, weight, spine, overlap, straightness) is not enough. Therefore, this paper suggests both the system that could describes the distribution of the arrow`s impact point into numerical representation and the correlation model between characteristics of arrow and impact points. The inputs of the model are characteristics of arrow (spine, straightness). And the output is MAD (mean absolute distance) of triangular shaped coordinates that could be obtained from 3 times repeated shooting by changing knock degree 120. The input-output data is collected for learning the correlation model, and ANN (artificial neural network) is used for implementing the model.