Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Introductory overview: Optimization using evolutionary algorithms and other metaheuristics
Environmental models are used extensively to evaluate the effectiveness of a range of
design, planning, operational, management and policy options. However, the number of …
design, planning, operational, management and policy options. However, the number of …
Machine learning‐based surrogate modeling for urban water networks: review and future research directions
Surrogate models replace computationally expensive simulations of physically‐based
models to obtain accurate results at a fraction of the time. These surrogate models, also …
models to obtain accurate results at a fraction of the time. These surrogate models, also …
[HTML][HTML] Lessons from a decade of adaptive pathways studies for climate adaptation
Adaptive pathways planning is an approach that maps the solution space over time to inform
decision making under uncertainty. Since its first applications to climate change adaptation …
decision making under uncertainty. Since its first applications to climate change adaptation …
An uncertain future, deep uncertainty, scenarios, robustness and adaptation: How do they fit together?
A highly uncertain future due to changes in climate, technology and socio-economics has
led to the realisation that identification of “best-guess” future conditions might no longer be …
led to the realisation that identification of “best-guess” future conditions might no longer be …
Eight grand challenges in socio-environmental systems modeling
Modeling is essential to characterize and explore complex societal and environmental
issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling …
issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling …
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions
The development and application of evolutionary algorithms (EAs) and other metaheuristics
for the optimisation of water resources systems has been an active research field for over …
for the optimisation of water resources systems has been an active research field for over …
Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty
Climate change introduces substantial uncertainty to water resources planning and raises
the key question: when, or under what conditions, should adaptation occur? A number of …
the key question: when, or under what conditions, should adaptation occur? A number of …
[HTML][HTML] Decision making under deep uncertainties: A review of the applicability of methods in practice
MCB Stanton, K Roelich - Technological Forecasting and Social Change, 2021 - Elsevier
Deep uncertainties like environmental and socio-economic changes create challenges to
decision making. Decision Making under Deep Uncertainty (DMDU) methods are …
decision making. Decision Making under Deep Uncertainty (DMDU) methods are …
[PDF][PDF] Robust decision making (RDM)
RJ Lempert - Decision making under deep uncertainty: From …, 2019 - library.oapen.org
Robust decision making (RDM) Page 35 Chapter 2 Robust Decision Making (RDM) RJ Lempert
Abstract • The quest for predictions—and a reliance on the analytical methods that require …
Abstract • The quest for predictions—and a reliance on the analytical methods that require …
Robustness metrics: How are they calculated, when should they be used and why do they give different results?
Robustness is being used increasingly for decision analysis in relation to deep uncertainty
and many metrics have been proposed for its quantification. Recent studies have shown that …
and many metrics have been proposed for its quantification. Recent studies have shown that …