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Depending on the nature of the target, such models are either models of phenomena or models of data.
Integer-order impulsive differential equations have become important in recent years as mathematical models of phenomena in both physical and social sciences.
On the other hand, integer order impulsive differential equations have become important in recent years as mathematical models of phenomena in both the physical and social sciences.
On the other hand, integer order impulsive differential equations have become important in recent years as mathematical models of phenomena in both the physical and the social sciences.
On the other hand, impulsive differential equations have become important in recent years as mathematical models of phenomena in both the physical and the social sciences.
A weaker framework of ontological unification is categorial unity, wherein abstract categories such as causality, information, etc, are attached to the interpretation of the specific variables and properties in models of phenomena (see Cat 2001 and 2006).
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Individual-based Markov models allow simulation of phenomena which involve transitions of heterogeneous individuals between states over time.
The chapter discusses two examples of approximations in the modeling of phenomena.
This computation requires knowledge about the emitter's transmission power, the usage of an accurate propagation model, and a statistical model of phenomena such as background noise [22].
The main references on fractional calculus also point out the power and usefulness of this topic to the modeling of phenomena in a wide range of scientific fields.
Modeling of phenomena based on conventional mathematical tools (e.g., differential equations) is not appropriate for dealing with ill-defined and uncertain problems.
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