They are developing software to help grid managers make sense of all that real-time data, and even to forecast problems before they occur.
The new algorithm is tested on a nine-dimensional inventory forecasting problem.
Several linear and non-linear techniques have been proposed to solve the stock market forecasting problem.
Several models have been presented to solve the financial time series forecasting problem.
However, in a medium term forecasting problem, we cannot foresee the excessive annual horizon.
Several techniques are suggested here for the solution of this forecasting problem.
Two applications are presented: a nine-dimensional inventory forecasting problem and an eight-dimensional water reservoir problem.
In addition, we present few examples of modular approaches, which can be applicable for time series forecasting problem.
A photovoltaic energy forecasting problem of a micro grid SoS, traffic jams forecasting and a system of autonomous vehicles will be offered for case studies.
The proposed strategy is inserted inside the core a hybrid metaheuristic model, applied for learning patterns from an important mini/microgrid forecasting problem, the household electricity demand forecasting.
