基于信息扩散的稀疏数据插值算法

为了解决实际海洋观测资料中存在的零散、稀疏问题,提出了一种基于信息扩散思想的插值方法——正态扩散插值模型。该方法基于模糊映射思想,通过对稀疏数据点的信息进行模糊扩散和插值映射,进而实现有限数据点信息向其邻近区域点的概率插值。运用该算法思想和途径,建立了信息扩散插值正态模型。通过对海温资料的插值试验和对比分析,验证了该方法的合理性和有效性,可为海洋观测资料的客观分析和标准化处理应用提供实用方法和技术参考。

Interpolation technique for sparse data based on information diffusion

Accurate and reliable observations are very necessary for ocean science research,but there are not fixed observational stations for ocean.The low density of observations and the difficulties in data acquisition and information extraction have been the key technological problems for ocean science research and ocean environment support.To solve the difficulties of scattered and sparse observational data in ocean science, a new interpolation technique based on information diffusion idea was researched and presented in this paper. By fuzzy mapping route, the sparse data samples was diffused and mapped into corresponding fuzzy sets in the form of probability in the interpolation model, and the corresponding normal information diffusion algorithm model was established. By making the interpolation experiments on and comparative analysis of the sea surface temperature data, the rationality and validity of the normal model were validated, and an applied route and technique for impersonal analyses and standardization of the oceanic observational data was provided.