Many kinds of data can be viewed as consisting of a set of vectors, each of which is a noisy combination of a small number of noisy prototype vectors. Physically, these prototype vectors may correspond to different hidden variables that play a role in determining the measured data. For example, a gene’s expression is influenced by the presence of transcription factor proteins, and two genes may...

This paper reviews the recent studies and works dealing with probabilistic forecasting models their applications in smart grids. According to these studies, this tries introduce a roadmap towards decision-making under uncertainty grid environment. In way, it firstly discusses common methods employed predict distribution of variables. Then, how literature used for which uncertain parameters they...

This paper demonstrates how a binary prediction market is capable of achieving probabilistic renewable energy forecast. In markets, participants trade shares associated with the outcome unknown future events (here, production, as random variable), and instantaneous price represents probability outcome. The focus this study to exploit informational value in forecasting. To end, three different m...