The tool supports interface of Foresight Analytics Platform 9 or earlier.

Modeling in the Desktop Application

Modeling and forecasting in the desktop application are executed within a modeling container.

A modeling container is a repository object that is used to create mathematical models of processes (phenomena) and to execute calculations based on these models. Calculation results in solving of various types of problems:

Data research problems.
Forecast problems.
Controlling problems.
Optimal control problems.
Imitation problems, and so on.

Modeling and forecasting problems are solved by creating the following objects and setting up interaction between the following objects:

Models. They are used to calculate output variables by transforming input variables by statistical and mathematical methods. Calculations are made taking into account calendar frequency of the model (years, half-years, quarters, months and days).
Variables. They are used to get source data and save calculation results.
Metamodels. They are used to arrange a calculation chain and model objects in the required order, and to describe the logic of modeling an arbitrary problem or process.
Problems. They are used to execute consequential calculation of metamodel to get the output data in the output variables. After finishing the calculation the results are loaded to variables.
Modeling scenarios. They are used to create a series in the output variable, to which the data is saved after calculation.

Along with modeling objects, the container may include shortcuts to any other platform repository objects, such as reports, forms, and so on.

Modeling Process

Modeling process in the desktop application is a successive creating and setting up modeling container objects aimed at solving dynamic system mathematical modeling problems.

Modeling starts with creating of models that are used to transform data by various methods taking into account calendar frequency. The variables that contain source data and are used to return calculation results are added to a model.

The number and the parameters of variables and models depend on a modeling problem to be solved.

The existing models must be arranged in the order of their calculation. To do this, create a metamodel presented by the hierarchic sequence of various elements, which forms a calculation chain of a modeling problem. The chain may contain models, other calculation chains (metamodels) and folders, which help arrange the structure of the calculation chain.

Models included in a metamodel are calculated by the modeling problem. Calculating a modeling problem enables the user to get output data in final variables. A problem can be calculated by various scenarios that enable the user to get forecasts by output variables, for example, based on optimistic and pessimistic forecast of scenario variables.

After a problem is calculated, the data obtained can be analyzed. To do this, open the output variables report or view the calculation history.