Selection of coordinate measuring machines by the neural network method

In this paper, a method for the selection of coordinate measuring machines is developed first, a neural networks training algorithm with conditional attributes through gradually adding training examples is proposed as the neural networks machine learning model for the selection of coordinate measuring machines. A learning model using conditional attributes was used in this study, which divides a problem into either an attribute or a decision. Through the input of attribute values, the system can present the required decision by inference. With this model, the training of the system can produce acceptable results. This learning model is also used to establish a multiple decision type selection system for coordinate measuring machines to assist the user in choosing an appropriate coordinate measuring machine.