Fuzzy information granulation transfers the time series analysis from numerical platform to granular platform, which enables us study at a different granularity. In previous studies, each fuzzy granule in can reflect average, range, and linear trend characteristics of data corresponding window. order get more general granule, this paper proposes polynomial granules, both nonlinear The distance ...

Abstract The power load prediction can ensure the supply and dispatch, which will be useful for market participants to plan make strategic decisions enhance reliability, save operation maintenance costs. Short-term data series have obvious approximate periodicity, while long-term show variability dynamic features. In addition, time of various modalities, such as reports production management da...

The spatio-temporal pattern recognition of time series data is critical to developing intelligent transportation systems. Traffic flow are that exhibit patterns periodicity and volatility. A novel robust Fourier Graph Convolution Network model proposed learn these effectively. includes a Embedding module stackable Spatial-Temporal ChebyNet layer. development the based on analysis theory can cap...