Network models are used to generate synthetic graphs with interesting features. These models allow to better understand the topology of the networks that we observer in the real world. One of the most basic models to generate random graphs is the Erdős–Rényi model. The following code creates a synthetic network with 100 nodes and 500 links: Network network = new ErdosRenyiNetwork(100, 500); It's that simple! We can generate networks using more complex models, such as the Watts–Strogatz model. In this example, we are going to generate a network with 100 nodes and 300 links. In the Watts-Stogatz model, we need to specify the probability of rewire for links. We will set this value to 0.2, as shown in the following code snippet: Network network = new WattsStrogatzNetwork(100 , 300, 0.2);Besides these ones, you can find more random network formation models in NOESIS, under the model/random package. All these models can be used as shown in the previous examples, instantiating the corresponding class indicating the desired value for each of the parameters required by the model.In addition to these random models, NOESIS is also able to generate different types of regular graphs, where all vertices have the same number of neighbors. These models can be found in the model/regular package, and their usage is rather similar to random models. For example, we can generate a grid of 5 rows and 10 columns as follows:Network network = new MeshNetwork(5,10); |

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