Dynamic Implement Radial Basis Function Networks

• Main Author: 林祐宇
• Other Authors: Tsai,Yen lung
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/64084175049885455739

碩士 === 國立政治大學 === 應用數學研究所 === 98 === During recent years, applying Radial Basis Function Networks (RBFN) to time series problems yields many important results. In this thesis, we try to implement a cross-platform computer tool that can easily construct a RBFN applied to time series forecasting problems. Moreover, the RBFN created by this computer tool can do real-time modification to fit specific needs. We first review the basic structures of RBFN and explain how it can be applied to time series problems. Then, we survey on so called temporal radial basis function (T-RBF) model, which draws much attention these years. Finally, we explain how we use Adobe Flex to create a computer tool as we mentioned in the beginning. The computer application is cross-platform and is suitable for both cloud computing and desktop applications.