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Compared to a known future nonstationary hydrology, incorporating uncertain nonstationary climate results in higher levees being planned for observed severe hydrology scenarios in later stages.
The central purpose of this study is to provide a framework for incorporating uncertain ecological input data into algorithms for designing networks of marine reserves.
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This approach incorporates uncertain random simulation into branch and bound algorithm.
To incorporate uncertain parameters, we apply the concept of minmax robust multi-objective optimization for designing sustainable energy supply systems.
Within this framework, the standard perturbation-based stochastic finite element method is relaxed in order to incorporate uncertain probabilities in static, dynamic and modal analyses.
The proposed model incorporates uncertain data for the ambient temperature, energy demands and prices of the local energy market, which are predicted through forecasting methods for determining the financial and environmental risks.
Based on the Kalman Filter methodology, in which distributed uncertain model results are corrected by assimilating measurement data from a reference system, the ES incorporates uncertain parameter values, associated model results, and measurement data into an update algorithm to provide an updated, corrected model state that approaches the reference system state.
The example is extended to incorporate uncertain actual logistics data.
Recently, because of the significance of uncertainty, more researchers have incorporated uncertain parameters into CLL networks.
On the other hand, the BME method used in this study has the significant feature that it is able to rigorously incorporate uncertain information of various kinds and different scales with the minimum number of theoretical assumptions.
To take into account the randomness of waves and complex structural responses, these failures need to be stochastically evaluated by incorporating various uncertain design factors.
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