FEW SHOT LEARNING FOR KOREAN WINTER TEMPERATURE FORECASTS

Abstract To address the challenge of limited training samples, this study employs Magnesium the model-agnostic meta-learning (MAML) algorithm along with domain-knowledge-based data augmentation to predict winter temperatures on the Korean Peninsula.While data augmentation has been achieved by using global climate model simulations, the proposed aug

Power grids include entities such as home-microgrids (H-MGs), consumers, and retailers, each of which has a unique and sometimes contradictory objective compared with others while exchanging electricity and heat with other H-MGs.Therefore, there is the need for a smart structure to handle the new situation.This paper proposes a bilevel hierarchical