国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Abstract：Abstract: Support vector machine is a machine learning algorithm based on statistical theory. It has advantages in solving high-dimensional, local extremum and structure selection problems. It is widely used in machine learning and data mining. However, the selection of its kernel width and penalty factor is directly related to the classification results of support vector machine. To solve the above problems, using the optimization algorithm to optimize the parameters can improve the classification accuracy of support vector machine to a certain extent. Chicken swarm optimization algorithm is a new global optimization algorithm proposed in recent years. It has clear structure and excellent global search ability. It is widely used in optimization problems. Based on this, a support vector machine model based on chicken swarm optimization (CSO-SVM) is proposed and is used to evaluate the bearing health status. The results show that the accuracy of bearing health state evaluation based on CSO-SVM is 97%, which is much higher than that of the health state model based on traditional machine learning model, and has better health state recognition effect.