Multi-Task Fusion Deep Learning Model for Short-Term Intersection Operation Performance Forecasting

A Deep Learning Framework for Short-term Power Load Forecasting

The scheduling and operation of power system becomes prominently complex and uncertain, especially with the penetration of distributed power. Load forecasting matters to the effective operation of power system. This paper proposes a novel deep learning framework to forecast the short-term grid load. First, the load data is processed by Box-Cox transformation, and two parameters (electricity pri...

A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

Deep Model Based Transfer and Multi-Task Learning Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

A central theme in learning from image data is to develop appropriate representations for the specific task at hand. Traditional methods used handcrafted local features combined with high-level image representations to generate image-level representations. Thus, a practical challenge is to determine what features are appropriate for specific tasks. For example, in the study of gene expression p...

Multi-task learning with deep model based reinforcement learning

In recent years, model-free methods that use deep learning have achieved great success in many different reinforcement learning environments. Most successful approaches focus on solving a single task, while multi-task reinforcement learning remains an open problem. In this paper, we present a model based approach to deep reinforcement learning which we use to solve different tasks simultaneousl...

Combination Model for Short-Term Load Forecasting

Gas demand possesses dual property of growing and seasonal fluctuation simultaneously, it makes gas demand variation possess complex nonlinear character. From previous studies know single model for nonlinear problem can’t get good results but accurately gas forecast were essential part of an efficient gas system planning and operation. In recent years, lots of scholar put forward combination mo...