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Following to methodology configuration, a proposal for optimization methods is discussed and a case study for comparing biomass network scenarios in mountainous city is introduced.
Table 1 Network dimensioning methodology (configuration #1) a This is an integer-programming problem for which analytic expressions of the blocking probabilities cannot be derived and, therefore, they have to be calculated numerically.
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In this methodology, the configuration modification is regarded as an inverse eigenvalue problem in which necessary changes of a set of configuration parameters are determined for achieving a desired natural frequency variation relative to the original design value.
Such a methodology enables configuration selection and parametric optimization to be implemented simultaneously.
The theoretical electronic behavior was evaluated to support the experimental findings, based on ZINDO/S methodology at configuration interaction with single excitations (CIS) level.
The complexes coordination geometries were optimized using the sparkle/PM6 model and the theoretical spectrophotometric studies were carried out in order to validate the experimental findings, based on ZINDO/S methodology at configuration interaction with single excitations (CIS) level.
The methodology for configuration #2 can be derived similarly to the previous one.
The detailed evaluation methodology and configurations of UMi can be found in [9].
The rest of this article is organized as follows: Section 2 describes the system-level simulation assumptions providing details on the evaluation methodologies, system configuration, simulation flow, and control overhead calculation.
A simple and novel methodology for the configuration of robust and distinct load signatures is presented in this paper.
The DRRC units are developed based on the methodology of neuron configuration, i.e., one neuron or multiple neurons.
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