System Simulation Geoffrey Gordon Pdf BETTER
System Simulation Geoffrey Gordon Pdf
Cheever [1] has noted that a lot of specialists that do work on system simulation “are not being realistic about the nature of the systems they model-system parameters are often set to grossly unrealistic values, the models are often set up to work in a way that is useful only for the very specific problems they are designed to address, and they are not addressing the routine problems management faces”. As an example of the latter he quotes the simulation of fisheries against a backdrop of exponential growth in human population. While his comments may be right they can also be connected to what system sim is used for in the first place, are the barriers being set up by the modeling community be “realistic” or are they generative and given a credible real world? In a related topic Atkinson et al. [2] found that “in some fieldwork communities, these small, real-world communities, with their easily handled problems, were the best training ground for practitioners to learn the techniques, styles and modes of work required for conducting larger, complex, more difficult social science studies”. The above-cited work influences our work here with three significant strands: (i) “In this paper we present the development of a general uncertainty propagation model (PURSE) for system simulations”; (ii) “A variety of user interface programs have been created that use the PURSE model described in this paper to facilitate the examination of the probability of success in conservation and resource management decisions made by managers”; (iii) “Our work builds an appreciation for and establishes the boundaries of the domain of system simulation in education and conservation and management.”
CADE is built around the work of Billington [3] who argued that any sound field simulation modelling should use “the rules of probability, statistics and mathematics of the problem being modelled”. This challenge has been taken up in the domain of system simulation as: “Behavioural agents in complex dynamic models should be modelled as stochastic processes to ensure that their decisions are not affected by idiosyncratic events such as the weather. In the development of such models, one of the major obstacles is to ensure the prescribed degree of realism, given the modeller’s perception of the physical and biological parameters of the problem.
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