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Flexibility for continuous improvement, flexibility for trouble control, flexibility for work force control, and flexibility for work-in-process control are quantified by using fuzzy present worth analysis.
The basic equations of engineering economics, including time value of money, present worth analysis, and life cycle costing, are also discussed in this chapter.
The sequential data worth analysis framework is examined by a number of cases, including under different irrigation intensities, with different prior data (existing observations that have already been collected), and with data of various depths and different measurement errors.
Create a personal balance sheet and net worth analysis.
Moreover, in our case, the interaction between the weak cationic PEG and the negatively charged DNA might also influence the ion mobility, which is worth analysis in the following work.
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In this work, we propose an efficient Bayesian data-worth analysis using a multilevel Monte Carlo (MLMC) method.
A data-worth analysis identifies the most valuable observation data to be measured for the best prediction of total hydrocarbon production.
Data-worth analysis is targeted to the quantification of the impact of new potential measurements on the expected reduction of predictive uncertainty based on a given process model.
We propose a new and computationally efficient data-worth analysis and quantification framework keyed to the characterization of target state variables in groundwater systems.
Since the Bayesian data-worth analysis involves a great deal of expectation estimation, the cost saving of the MLMC in the assessment can be outstanding.
Design of a cost-effective data collection scheme, i.e., data-worth analysis, requires quantifying model parameter, prediction, and both current and potential data uncertainties.
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