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Simulation, in the broadest sense, has been used to mean imitation. Simulations and models as well have been used as abstractions of reality. Simulations have been used to deliberately emphasize a part of the reality at the expense of others because of computer power limitations. Simulation has been used in order to focus the audience on a vital aspect of the simulation in question. On the other hand, models are logical, mathematical or structured representation of the realities. As a result, simulations are specific applications of models in order to reach at some outcome. While some field biologists have claimed that laboratory simulations and mathematical models can never capture the variability and complexity of the real world, experimental scientists have retorted by claiming that simulations and complex models have many simultaneous variables which allow for meaningful analysis (Zipfel, 2007).
The experimental scientists’ views that complex models and simulations indeed have simultaneous variables which allow for meaningful analysis should be supported. This is because the use of complex models and simulations allow the users to be able to study and analyze the performance and behavior of theoretical or actual systems. The use of simulations also allow studies to be performed on models of the system established for the aim of studying specific system characteristics and dynamics rather than perform the studies on the real world systems. By so doing, the complexity and variability that occur in such models and simulations can easily be captured and rectified on real systems. Losses or other negative impacts which can happen on such systems can therefore be easily rectified in simulations and models before they are implemented on the real systems (Velten, 2009).
The use of complex models and simulations should be encouraged because they have many simultaneous variables which can give room for analyzing of meaningful data or information in any given case. Users are thus able to draw conclusions regarding the real system through studying and analyzing of the models and simulations.