Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter
径向基函数网络与动态加权粒子滤波的海表温度建模
The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically…