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Parameter optimization for chemical systems requires generation of initial guesses. These parameters should be generated using systematic sampling of parameter space, minimizing differences between output data and the corresponding reference data. In this paper we discuss the ParamChem project, which is creating reusable and extensible infrastructure for the computational chemistry community that will reduce unnecessary and eliminate redundancies in parametrized computations using modern software engineering tools.
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Ghosh et al. (2011) studied this question.
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