lmproved interpolation technique and its appl ication in sparse SST time series data fitting based on information diffusion model
To tackle sparse observed data in asymmetrical and abnormal distribution and the problem of small sample,a new interpolation technique based on the information diffusion and optimal window width theory was improved by genetic algorithm in this paper.With fuzzy mapping route,the scattered samples can be diffused and mapped into corresponding fuzzy sets in the form of probability.By interpolating monthly sea surface temperature time series from National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR)reanalysis,the rationality and validity of the improved information diffusion model was validated using different size of samples.The conventional information diffusion models were also introduced for comparison.All results show the new idea and technique may be a-vailable for interpolating such incomplete time series in ocean science or imperfect information condition.
sparse datainformation diffusionwindowing of optimal information diffusiongenetic algo-rithminterpolation
NETL
NSTL
万方数据
维普
