Physica A

p.276-283Recent studies have focused on models to simulate the complex phenomenon of evolution of species. Several studies have been performed with theoretical models based on Darwin’s theories to associate them with the actual evolution of species. However, none of the existing models include the affinity between individuals using network properties. In this paper, we present a new model based on the concept of affinity. The model is used to simulate the evolution of species in an ecosystem composed of individuals and their relationships. We propose an evolutive algorithm that incorporates the degree centrality and efficiency network properties to perform the crossover process and to obtain the network topology objective, respectively. Using a real network as a starting point, we simulate its evolution and compare its results with the results of 5788 computer-generated networks

Physica A

p.81-84In this paper, we studied density effects in semantic networks constructed from a database of titles of papers published in scientific journals as a parameter to indicate the diversity of concepts in a journal. The proposed method essentially consists of fixing the number of titles for all of the studied scientific journals and analyzing the behavior of the density variation curves with regard to the inclusion of cliques (that is, complete networks associated with the titles). We observed that density behaves as a critically self-organized object when titles (cliques) are included in the network

Physica A

p.276-283Recent studies have focused on models to simulate the complex phenomenon of evolution of species. Several studies have been performed with theoretical models based on Darwin’s theories to associate them with the actual evolution of species. However, none of the existing models include the affinity between individuals using network properties. In this paper, we present a new model based on the concept of affinity. The model is used to simulate the evolution of species in an ecosystem composed of individuals and their relationships. We propose an evolutive algorithm that incorporates the degree centrality and efficiency network properties to perform the crossover process and to obtain the network topology objective, respectively. Using a real network as a starting point, we simulate its evolution and compare its results with the results of 5788 computer-generated networks

Physica A

p.276-283Recent studies have focused on models to simulate the complex phenomenon of evolution of species. Several studies have been performed with theoretical models based on Darwin’s theories to associate them with the actual evolution of species. However, none of the existing models include the affinity between individuals using network properties. In this paper, we present a new model based on the concept of affinity. The model is used to simulate the evolution of species in an ecosystem composed of individuals and their relationships. We propose an evolutive algorithm that incorporates the degree centrality and efficiency network properties to perform the crossover process and to obtain the network topology objective, respectively. Using a real network as a starting point, we simulate its evolution and compare its results with the results of 5788 computer-generated networks