In many aspects, our world is very complex. It is defined by a huge number of interconnected phenomena, which involve different dimensions such as economic, social, cultural, philosophical, biological and physical dimensions. Of course, this concept has been documented sufficiently in a general context. However, the mathematical perspective is important to present a clear scientific view of those complex problems.
In the present time, two of the most important approaches to tackle complex systems are probability and stochastic processes theory. Still from an analytic perspective, modeling and solving a problem using a stochastic approach is not a trivial issue. Hence, a combination of the logic of probabilistic reasoning with computational science is needed to obtain qualitatively good solutions in a reasonable time.
The computational probability and the stochastic processes have varied classifications on issues such as random walks, random matrix, Markov chains, martingales, Gaussian processes, Lévy processes, random fields, and renewal and branching processes and therefore can be applied in a broad action field, which covers different disciplines in applied science.
This Research Topic is particularly focusing on applications of computational probability and/or mathematical modeling oriented to stochastic processes. Potential scenarios and/or applications include, but are not limited to:
• Bioinformatics
• Systems Biology
• Phenomenological studies in physics and earth science
• Industrial engineering: production, inventories control, quality, among others
• Finance
In many aspects, our world is very complex. It is defined by a huge number of interconnected phenomena, which involve different dimensions such as economic, social, cultural, philosophical, biological and physical dimensions. Of course, this concept has been documented sufficiently in a general context. However, the mathematical perspective is important to present a clear scientific view of those complex problems.
In the present time, two of the most important approaches to tackle complex systems are probability and stochastic processes theory. Still from an analytic perspective, modeling and solving a problem using a stochastic approach is not a trivial issue. Hence, a combination of the logic of probabilistic reasoning with computational science is needed to obtain qualitatively good solutions in a reasonable time.
The computational probability and the stochastic processes have varied classifications on issues such as random walks, random matrix, Markov chains, martingales, Gaussian processes, Lévy processes, random fields, and renewal and branching processes and therefore can be applied in a broad action field, which covers different disciplines in applied science.
This Research Topic is particularly focusing on applications of computational probability and/or mathematical modeling oriented to stochastic processes. Potential scenarios and/or applications include, but are not limited to:
• Bioinformatics
• Systems Biology
• Phenomenological studies in physics and earth science
• Industrial engineering: production, inventories control, quality, among others
• Finance
