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Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies.
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A systematic probabilistic framework is presented here for detailed estimation and optimization of the life-cycle cost of engineering systems.
The estimation of the beam characteristics is very important for the enhancement and optimization of the beam power.
The empirical Bayes approach utilizes a combination of E-M and PSO algorithms for estimation and optimization in detection of the differential Pol II binding in two biological conditions.
The estimation of the expected load profile of the village and optimization of the system is done using hybrid optimization model for electrical renewable (HOMER) software.
We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes.
Efficient small axial turbine design requires precise loss estimation and geometry optimization of turbine blade profile for maximum performance.
Typically, optimization-based techniques are used for the estimation of nonmeasurable parameters of such biological processes [ 4, 27, 28].
The particle swarm-based multistep nonlinear optimization algorithm proposed in the present work was used for the estimation of 23 parameters of an eleven-dimensional nonlinear system (the pathways identification was not considered).
A thorough quantitative evaluation and optimization of the M-EPI sequence is beyond the scope of this manuscript, however, we did compare probabilistic fiber orientation estimation as it depended on the different m×n accelerations for a HARDI acquisition.
Most efforts are generally dedicated to the comparison of methodologies and their optimization for the estimation of soil properties.
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