Now we are going to explain the various Graphical Models Applications in real life such as – Manufacturing, finance, Steel Production, Handwriting Recognition etc. At last, we will discuss the case study about the use of Graphical Models in the Volkswagen.
Let us now see few applications of graphical models:
Making the production of low cost and most reliable components at a high rate is possible. If all components of a production system (i.e. machine tool operation, dispatching etc) work on optimized parameters. Compute this by using graphical models.
Graphs, because they are pictures. They are particularly appropriate for presentation of financial information. Presenting financial information requires a careful understanding of both “what you want to say” and “who you need to say it to“.
To calculate the emission of carbon dioxide for Steel’s deoxidation we use Graph model.
We can use Graphical models to recognize hand writing. It can also use in several applications. It uses hand writing for identification.
We use Graphical models for diagnosing issues in it. It is used for help and to resolve them.
Graphical models provide a powerful framework for encoding. It provides the statistical structure of visual scenes. It also provides developing corresponding learning and inference algorithms.
Let us see the application of graphical model at Volkswagen:
To attempt to achieve the ideal situation in which the customers provided by customized products built. By using components that arrive ‘‘just-in-time’’ for assembly, so that no stock is necessary at all. For this to be possible, it is necessary to plan the production process with high precision. This requires most accurate prediction of supply of the components.
To create the relational model it needs 3 steps:
i) Translate the catalog of technical and marketing rules into a relational representation. Represent All rules that refer to the same set of attributes by a relation over this set. Starting from the Cartesian product of the attribute domains, discard all tuples that are incompatible with one of the rules.
ii) Organize these relations in a lattice structure defined by the subset relation on the domains of the relations. Use the maximal elements of the resulting lattice as the maximal cliques of the graph of a relational graphical model. Turn the relational model into an undirected graphical model by taking the graph structure of the relational model. Estimate and enhance it with probabilistic distribution functions, from a sales database.
iii) Turn the relational model into an undirected graphical model by taking the graph structure of the relational model. Estimate and enhance it with probabilistic distribution functions, from a sales database.