徑向基函數(shù)神經(jīng)網(wǎng)絡曲面數(shù)據(jù)破損修補

本文針對工業(yè)零件設計中曲面數(shù)據(jù)的破損問題，提出了一種基于徑向基函數(shù)(RBF)神
經(jīng)網(wǎng)絡的數(shù)據(jù)修補方法。闡述了數(shù)據(jù)修補方法的原理，設計了網(wǎng)絡結構和訓練算法，運用K均值算法實現(xiàn)隱層節(jié)點的中心初始化。通過兩種曲面的數(shù)據(jù)進行訓練，并對此兩種曲面數(shù)據(jù)破損進行修補，結果表明，本文提出的曲面數(shù)據(jù)破損修補方法是有效的。
關鍵詞: 曲面破損 數(shù)據(jù)修補 徑向基函數(shù)神經(jīng)網(wǎng)絡
Curved Surface Insufficient Data Mending Using RBF Neural Network Yan Juan1 Wu Yuzhi2
1. College of Computer and Information Technology, Henan Normal University 2. Department of Computer, Jiaozuo University Abstract. The paper proposes a curved surface data mending method aimed to the problem of insufficient data in the modern industry based on the radial basis function(RBF) neural network. Introduces the theory of data mending. Designs the configuration and train algorithm of the network. Uses the K-means to initialize the points input of hidden-lay. Trains the neural network and does mending examination through two groups of curved surface data. The results show that the method proposes in the paper is efficient.
Key Words insufficient curved surface, data mending, RBF neural network