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This paper presents the proposal of a generic model of stochastic process based on neural networks, called Neural Stochastic Process (NSP). The proposed model can be applied to problems involving phenomena of stochastic behavior and / or periodic features. Through the NSP's neural networks it is possible to capture the historical series' behavior of these phenomena without requiring any a priori information...
We introduce a novel evolutionary formulation of the problem of finding a maximum independent set of a graph. The new formulation is based on the relationship that exists between a graph’s independence number and its acyclic orientations. It views such orientations as individuals and evolves them with the aid of evolutionary operators that are very heavily based on the structure of the graph and its...
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