Journal articles on the topic 'Scenario uncertainty'
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1
Pollack-Johnson, Bruce, and Matthew J. Liberatore. "Project Planning under Uncertainty Using Scenario Analysis." Project Management Journal 36, no. 1 (March 2005): 15–26. http://dx.doi.org/10.1177/875697280503600103.
Abstract:
An important component of risk management relates to project schedule uncertainty. To address this issue, a scenario (i.e., macro-level approach) for modeling and analyzing projects with significant uncertainty in their network structure and/or durations of some activities is presented. This approach requires that a set of project network scenarios is able to be identified, each with an assessed probability of occurrence. These scenarios might differ according to the results of uncertain events that could occur during the course of the project, uncertain activity durations (whether independent or dependent), finite loops where repeated activities can have different durations, or a combination of these. Advantages of our approach include the use of standard methods and software, as well as greater accessibility to, and likelihood of, the use of uncertainty analysis in project planning. Several examples are used to illustrate the suggested approach.
2
Jansen van Vuuren, David. "Valuing specialised property: cost vs profits method uncertainty." Journal of Property Investment & Finance 34, no. 6 (September 5, 2016): 655–63. http://dx.doi.org/10.1108/jpif-06-2016-0048.
Abstract:
Purpose The purpose of this paper is to compare the value outcomes of the cost approach to the DCF profits method when valuing specialised property under different scenarios as a test for choice of method or model uncertainty; and to quantify valuation uncertainty under each scenario and to argue for an increasing adoption of the profits method of valuation. Design/methodology/approach A qualitative case study approach was used to analyse four physical valuations performed in practice under four specific scenarios, namely, a business-as-usual scenario, an underperforming business scenario, an expanding capacity scenario and a combined business-as-usual funding a start-up joint venture scenario. Findings The cost approach relative to the DCF profits approach consistently under-values specialised property under business-as-usual and business expanding scenarios while it over-values in instances of underperforming business scenario. Practical implications Financial institutions that predominantly uses or accepts the cost approach for valuing specialised property should consider adopting the DCF profits approach as the default approach when valuing for mortgage lending purposes. Business owners of specialised properties should contract practitioners knowledgeable and skilled in the application of the DCF profits method. Originality/value This paper quantifies choice of method or model uncertainty of four different scenarios of specialised properties where both the cost approach and DCF profits methods of valuation were employed. It suggests the adoption of the DCF profits method as the default method of valuation for specialised property.
3
Cambou, Mathieu, and Damir Filipović. "MODEL UNCERTAINTY AND SCENARIO AGGREGATION." Mathematical Finance 27, no. 2 (June 19, 2015): 534–67. http://dx.doi.org/10.1111/mafi.12097.
4
Yip, Stan, Christopher A. T. Ferro, David B. Stephenson, and Ed Hawkins. "A Simple, Coherent Framework for Partitioning Uncertainty in Climate Predictions." Journal of Climate 24, no. 17 (September 2011): 4634–43. http://dx.doi.org/10.1175/2011jcli4085.1.
Abstract:
A simple and coherent framework for partitioning uncertainty in multimodel climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty, and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model–scenario interaction—the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the twenty-first century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multimodel ensembles. For example, three models show a diverging pattern over the twenty-first century, while another model exhibits an unusually large variation among its scenario-dependent deviations.
5
Mo, Mingshan, Xinrui Xiong, Yunlong Wu, and Zuyao Yu. "Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties." Energies 16, no. 22 (November 20, 2023): 7669. http://dx.doi.org/10.3390/en16227669.
Abstract:
A community-integrated energy system under a multiple-uncertainty low-carbon economic dispatch model based on the deep reinforcement learning method is developed to promote electricity low carbonization and complementary utilization of community-integrated energy. A demand response model based on users’ willingness is proposed for the uncertainty of users’ demand response behavior; a training scenario set of a reinforcement learning agent is generated with a Latin hypercube sampling method for the uncertainties of power, load, temperature, and electric vehicle trips. Based on the proposed demand response model, low-carbon economic dispatch of the community-integrated energy system under multiple uncertainties is achieved by training the agent to interact with the environment in the training scenario set and reach convergence after 250 training rounds. The simulation results show that the reinforcement learning agent achieves low-carbon economic dispatch under 5%, 10%, and 15% renewable energy/load fluctuation scenarios, temperature fluctuation scenarios, and uncertain scenarios of the number of trips, time periods, and mileage of electric vehicles, with good generalization performance under uncertain scenarios.
6
Engelberg, Daniel. "The value of scenario discovery in land-use modeling: An automated vehicle test case." Journal of Transport and Land Use 17, no. 1 (May 9, 2024): 321–49. http://dx.doi.org/10.5198/jtlu.2024.2401.
Abstract:
Long-range planning is an uncertain endeavor. This is especially true for urban regions, small ships in a global urban storm that are too small to influence macro policies and without the land-use powers of local governments. Exploratory scenarios, the established practice for planning under deep uncertainty, have inspired stakeholders to consider multiple futures but have fallen short of identifying robust and contingent policies. We need new tools to plan under conditions of deep uncertainty. Scenario discovery is a technique for using simulation models to explore the performance of policy options across uncertain scenarios. This paper presents an application of scenario discovery in land-use modeling and asks what this computationally intensive approach offers relative to a more circumscribed exploration of uncertainty space. The introduction of autonomous vehicles (AVs) and their associated impacts on land use provide a test case demonstrating this method, as well as a topic of substantive concern. This research concludes that scenario discovery is particularly valuable for identifying the conditions under which contingent policies are likely to succeed. In terms of AV policy, this research establishes that forward-thinking, transit-oriented-development strategies can mitigate spatial dispersion while also reducing overall housing costs. In addition, I find that AVs may blunt the impacts of some current policy tools if they extend the distance individuals are willing to travel to work.
7
Choi, Byung-Cheon, and Myoung-Ju Park. "Min-Max Regret Version of the Linear Time–Cost Tradeoff Problem with Multiple Milestones and Completely Ordered Jobs." Asia-Pacific Journal of Operational Research 32, no. 05 (October 2015): 1550039. http://dx.doi.org/10.1142/s0217595915500396.
Abstract:
We consider a linear time–cost tradeoff problem with multiple milestones and uncertain processing times such that all jobs are completely ordered. The performance measure is expressed as the sum of total weighted number of tardy jobs and total crashing cost. The processing times uncertainty is described through two types of scenarios: discrete and interval scenarios. The objective is to minimize maximum deviation from optimality over all scenarios. For the discrete scenario case, we prove its NP-hardness, develop a pseudo-polynomial time approach, and present a polynomially solvable case. Finally, we show that the interval scenario case is also NP-hard.
8
Carneiro, Joana, Dália Loureiro, Marta Cabral, and Dídia Covas. "Integrating Uncertainty in Performance Assessment of Water Distribution Networks by Scenario Building." Water 16, no. 7 (March 28, 2024): 977. http://dx.doi.org/10.3390/w16070977.
Abstract:
This paper presents and demonstrates a novel scenario-building methodology that integrates contextual and future time uncertainty into the performance assessment of water distribution networks (WDNs). A three-step approach is proposed: (i) System context analysis, identifying the main key factors that impact the WDN performance; (ii) Scenario definition, identifying the implicated WDN variables, describing its possible evolution, and conjugating them to further establish the reference scenario and the two most relevant and opposite ones; and (iii) Scenario modelling, simulating the WDN behaviour for those scenarios. The obtained spatial and temporal hydraulic results are further used to calculate performance metrics. The methodology is applied to a real WDN to assess resilience performance considering infrastructure asset robustness (real water loss performance indicator), service reliability (minimum pressure index), and service flexibility (network resilience index). A new formulation to assess the metric evolution over time is proposed, deducting the further-away performance results by using an uncertainty weight. The results demonstrate that the increase in metric amplitude for the opposite scenarios over time highlights future uncertainty, reflecting context uncertainty, and the comparison of metric spatial distribution (i.e., at the pipe/node levels) highlights critical areas with higher associated uncertainty.
9
Smorkalova, Tatyana L., Lyudmila V. Tarasova, and Olga S. Solodukhina. "GENDER-SPECIFIC LIFE SCENARIOS IN INDIVIDUALS WITH DIFFERENT LEVELS OF TOLERANCE TO UNCERTAINTY." Russian Journal of Education and Psychology 14, no. 5 (October 31, 2023): 109–25. http://dx.doi.org/10.12731/2658-4034-2023-14-5-109-125.
Abstract:
Purpose. Currently, the scenario line of research in personality psychology seems to be particularly promising, since this line of research allows us to identify the specific features of the transformation of the conscious construction of human life paths under changing conditions of uncertainty. The aim of the study is to determine the gender specificity of life scenarios in individuals with different levels of tolerance to uncertainty.
Materials and Methods. The sampling consisted of 200 people with different levels of tolerance towards uncertainty. The methods of the study included the semantic differential Lifestyle by V.P. Serkin and the New Questionnaire of Tolerance Towards Uncertainty by T.V. Kornilova. The data obtained were processed by means of factor analysis with the help of the program IBM SPSS Statistics 23.
Results. The results showed that the life scenarios of people with different levels of tolerance to uncertainty are gender-specific: men with a high tolerance to uncertainty show predominant characteristics of the scenario associated with an active life position and the search for novelty, whereas women show a scenario aimed at activity in the social sphere (the desire to actively participate in the fate of others, to help and support). Men with a low tolerance towards uncertainty show such scenario patterns as striving for security, stability and predictability of events, while women – in addition to striving for a convenient, comfortable life – show tactical patterns: emotional restraint and calculation.
Field of results application. The results of the study can be used in socio-psychological training and counselling to identify and correct an individual’s life scenario.
10
Marzeion, B., A. H. Jarosch, and M. Hofer. "Past and future sea-level change from the surface mass balance of glaciers." Cryosphere Discussions 6, no. 4 (August 6, 2012): 3177–241. http://dx.doi.org/10.5194/tcd-6-3177-2012.
Abstract:
Abstract. We present a model of the global surface mass balance of glaciers, based on the reconstruction and projection of the surface mass balance of all the world's individual glaciers. The model is validated using a leave-one-glacier-out cross validation scheme using 3997 observed surface mass balances of 255 glaciers, and against 756 geodetically observed, temporally integrated volume and surface area changes of 341 glaciers. Between 1902 and 2009, the world's glaciers are reconstructed to have lost mass corresponding to 114 ± 5 mm sea level equivalent (SLE). During the 21st century, they are projected to loose additionally between 148 ± 35 mm SLE (scenario RCP26), 166 ± 42 mm SLE (scenario RCP45), 175 ± 40 mm SLE (scenario RCP60), to 217 ± 47 mm SLE (scenario RCP85). Based on the extended RCP scenarios, glaciers are projected to approach a new equilibrium towards the end of the 23rd century, after having lost between 248 ± 66 mm SLE (scenario RCP26), 313 ± 50 mm SLE (scenario RCP45), to 424 ± 46 mm SLE (scenario RCP85). Up until approximately 2100, ensemble uncertainty within each scenario is the biggest source of uncertainty for the future glacier mass loss; after that, the difference between the scenarios takes over as the biggest source of uncertainty. Rates of mass loss are projected to peak between 2050 and 2100, depending on the scenario.
11
de Sousa, J. Ricardo Tavares, and Aya Diab. "UNCERTAINTY ANALYSIS FOR STATION BLACKOUT SCENARIO." Journal of Computational Fluids Engineering 24, no. 4 (December 31, 2019): 60–68. http://dx.doi.org/10.6112/kscfe.2019.24.4.060.
12
Tapinos, Efstathios. "Perceived Environmental Uncertainty in scenario planning." Futures 44, no. 4 (May 2012): 338–45. http://dx.doi.org/10.1016/j.futures.2011.11.002.
13
Zapata, Marisa A., and Nikhil Kaza. "Radical uncertainty: scenario planning for futures." Environment and Planning B: Planning and Design 42, no. 4 (January 2015): 754–70. http://dx.doi.org/10.1068/b39059.
14
CHUNG, DAE-YOUNG, and BYUNG-CHEON CHOI. "JUST-IN-TIME SCHEDULING UNDER SCENARIO-BASED UNCERTAINTY." Asia-Pacific Journal of Operational Research 30, no. 02 (April 2013): 1250055. http://dx.doi.org/10.1142/s0217595912500558.
Abstract:
This paper considers the single-machine scheduling problem, where job parameters are uncertain and the performance measure is to maximize the weighted number of just-in-time jobs, defined as jobs completed exactly on their due dates. Uncertainty is described through a finite set of well-defined scenarios. The criteria for this environment is to minimize the maximum deviation from optimality for all scenarios. We present the computational complexity results for several cases.
15
Mantel, S. K., D. A. Hughes, and A. S. Slaughter. "Water resources management in the context of future climate and development changes: a South African case study." Journal of Water and Climate Change 6, no. 4 (May 11, 2015): 772–86. http://dx.doi.org/10.2166/wcc.2015.098.
Abstract:
Modelling uncertainty under future climate change and socio-economic development is essential for adaptive planning and sustainable management of water resources. This is the first study in South Africa incorporating uncertainty within climate and development scenario modelling for understanding the implications on water availability through comparison of the resulting uncertainty. A Water Evaluation and Planning model application was developed for the Amatole system (South Africa), which consists of three catchments with inter-basin transfers. Outputs for three sets of scenarios are presented, namely development-only, climate-change-only and climate-and-development scenarios. Near future (2046–2065) development uncertainty was estimated from three scenarios (lower, intermediate and upper) and climate change uncertainty from nine downscaled global climate models under the A2 emissions scenario. Consideration of development increased the uncertainty associated with climate-change-only scenarios, particularly at low flows. Water deficits are projected in the future for the Amatole system as the present water infrastructure cannot meet water demands under the near future intermediate and upper development scenarios. The deficits are likely to be exacerbated by inclusion of environmental flows (not included in the model). The recommended strategy is that of adaptive management, in combination with continual monitoring of climate and development changes, for reducing future uncertainty.
16
Ingenbleek, PTM, HJ Blokhuis, A. Butterworth, and LJ Keeling. "A scenario analysis on the implementation of a farm animal welfare assessment system." Animal Welfare 20, no. 4 (November 2011): 613–21. http://dx.doi.org/10.1017/s0962728600003250.
Abstract:
AbstractThere have been important developments in the measurement of farm animal welfare in recent years. Measuring animal welfare is one thing, implementing a farm animal welfare assessment system another. The implementation of such a system occurs in an environment that is influenced by economic, political, technological and socio-cultural factors which interact with each other. This creates enormous complexity, generates a huge number of different potential ‘futures’, and makes the eventual impact that the system will have on the welfare of farm animals uncertain. This article draws upon strategic management literature to apply scenario analysis as a technique to help understand the variance of the uncertainty associated with the implementation of an animal welfare assessment scheme. Specifically, it develops two extreme scenarios based on a theoretical European-wide implementation: one scenario in which all uncertain factors influence the implementation of the assessment system in a negative way, and one scenario in which all these factors have positive impacts. These scenarios provide insight into the variance of possible futures in which the system may have to function. Although consumers are an important stakeholder group, their role in creating uncertainty for the system may be overestimated; it is apparent that the roles of companies, brands and certification organisations deserve significant attention, as well as any relevant institutional structure.
17
Schmitt Olabisi, Laura, Robert Ugochukwu Onyeneke, Onyinye Prince Choko, Stella Nwawulu Chiemela, Lenis Saweda O. Liverpool-Tasie, Anthonia Ifeyinwa Achike, and Adedapo Ayo Aiyeloja. "Scenario Planning for Climate Adaptation in Agricultural Systems." Agriculture 10, no. 7 (July 7, 2020): 274. http://dx.doi.org/10.3390/agriculture10070274.
Abstract:
Effective climate adaptation in sub-Saharan African agriculture will require coordination across multiple scales of governance. Decision-makers from local to national scales will be tasked with planning under conditions of high uncertainty, often with minimal data. Participatory scenario planning is a method for devising adaptation strategies under high uncertainty, and we hypothesized that it could also be used for identifying systemic, inclusive, and transformative adaptation options at the community scale, and for highlighting opportunities for cross-scalar collaboration. We conducted scenario exercises with two communities in southeastern Nigeria that have experienced increasing flooding and other challenges linked to climate variability. Both communities identified drivers of change that intersect with climate, as well as community-scale actions that would improve adaptation to a range of future scenarios. We found evidence that scenario exercises can stimulate communities to develop transformative approaches to climate adaptation that seek to reduce climate risk by creating new systems and processes. We also found that community-identified priorities for strategic action highlight how larger-scale interventions could coordinate with communities to adapt more effectively. Participatory scenario planning is therefore a potentially important tool for adaptation planning in regions in which future conditions are highly uncertain.
18
Josef, Hari Kusnanto, Dhanasari Vidiawati, Elsa Pudji Setiawati, Mariatul Fadilah, Armyn Nurdin, Syarhan Syarhan, Sintak Gunawan, and Mora Claramita. "Webinar Panelist RPCPE Serial Response to Pandemic Covid-19." Review of Primary Care Practice and Education (Kajian Praktik dan Pendidikan Layanan Primer) 5, no. 2 (September 22, 2022): 45. http://dx.doi.org/10.22146/rpcpe.74818.
Abstract:
Relaxation of PSBB Policy from the Perspective of Community Medicine and Epidemiology in IndonesiaWhen the government will do something meaningful and full of uncertainty, such as relaxation of the PSBB, it needs to be done based on a plan with uncertainty, namely scenario planning. In scenario development, four stages must be carried out, namely identifying the driving forces and critical uncertainties. Some scenarios then create a path for how a plan will travel.
19
Lee, Jae-Kyoung, and Young-Oh Kim. "Selection of representative GCM scenarios preserving uncertainties." Journal of Water and Climate Change 8, no. 4 (July 27, 2017): 641–51. http://dx.doi.org/10.2166/wcc.2017.101.
Abstract:
Abstract Climate change studies usually include the use of many projections, and selecting an essential number of projections is very important, because using all Global Climate Model (GCM) scenarios is impossible in practice. Furthermore, the climate change impact assessment is often sensitive to the choice of GCM scenarios. This study suggests that selecting the best-performing scenarios based on a historical period should be avoided in nonstationary cases like climate change, and then proposes a new approach that can preserve the uncertainty, that all scenarios contain. The new approach groups all GCM scenarios into several clusters, and then selects a single representative scenario among member scenarios of each cluster, based on their skill scores. The proposed approach is termed ‘selecting the principal scenarios’, and applied to select five principal GCM scenarios for the South Korean Peninsula, among 17 GCM scenarios of the 20C3M emission scenario. The uncertainty preservation is measured with the maximum entropy theory. The case study presents that the principal scenarios preserve the full range of total uncertainty, compared to less than 65% for the best scenarios confirming that preserving uncertainty with the principal scenarios is more adequate, than selecting the best-performed scenarios, in climate change studies.
20
Kravchenko, Olha. "ORGANIZATION OF FINANCIAL PLANNING IN THE UNCERTAINTY." International Journal of New Economics and Social Sciences 5, no. 1 (June 30, 2017): 17–28. http://dx.doi.org/10.5604/01.3001.0010.4254.
Abstract:
The article investigates a financial planning organization at enterprises in uncertainty. The financial planning mistakes, namely the organization of the planning work and proper planning, have been considered. The expediency of the scenario approach of planning in uncertainty has been substantiated. A financial planning technology based on the construction of enterprise scenarios has been proposed.
21
Nikbakht Nasrabadi, Alireza, Abbas Ebadi, Masoud Fallahi-Khoshknab, Soheil Najafi-Mehri, Farideh Yaghmaei, Fatemeh Alhani, Atefe Vaezi, Mansoureh Sepehrinia, and Mahboubeh Shali. "Future Scenarios of Nursing Education in Iran." Iran Journal of Nursing 36, no. 142 (June 1, 2023): 110–27. http://dx.doi.org/10.32598/ijn.36.142.1398.7.
Abstract:
Background & Aims One of the challenges in accurate and macro planning for the future is the uncertainty involved in estimating the future and rapid changes in various health-related fields. A powerful tool that can predict future competitive environments is the scenario planning tool. The current research aims to provide scenarios for the future of nursing education in Iran. Materials & Methods This exploratory research was conducted in 2022. In the first stage, the drivers and trends of nursing education were identified using meta-synthesis, interviews, and the Delphi method. Then, the influence and uncertainty of the identified trends were rated using the opinions of a panel of experts. In the next step, using influence/uncertainty diagrams, the key factors for writing the scenario were identified. Scenarios were then designed by Scenario Wizard software, version 4.11, and strategies were presented. Results The experts agreed on 6 drivers and 31 trends. With five key uncertainties, the scenarios were designed with three optimistic, realistic, and pessimistic assumptions. According to the size of the matrix and its dimensions (15×15), four problem-oriented, ethics-oriented, maintaining the status quo, and limited educational system scenarios were designed. The validity of the scenarios was examined according to feasibility, internal consistency, usefulness, and differentiability. Conclusion Each of the four designed scenarios has the potential to be realized, but their occurrence depends on the current plans. The use of future planning methods, such as the scenario planning tool, can be used as a warning system for awareness of opportunities and threats in Iran's health system before a crisis.
22
Marzeion, B., A. H. Jarosch, and M. Hofer. "Past and future sea-level change from the surface mass balance of glaciers." Cryosphere 6, no. 6 (November 12, 2012): 1295–322. http://dx.doi.org/10.5194/tc-6-1295-2012.
Abstract:
Abstract. We present estimates of sea-level change caused by the global surface mass balance of glaciers, based on the reconstruction and projection of the surface mass balance of all the individual glaciers of the world, excluding the ice sheets in Greenland and Antarctica. The model is validated using a leave-one-glacier-out cross-validation scheme against 3997 observed surface mass balances of 255 glaciers, and against 756 geodetically observed, temporally integrated volume and surface area changes of 341 glaciers. When forced with observed monthly precipitation and temperature data, the glaciers of the world are reconstructed to have lost mass corresponding to 114 ± 5 mm sea-level equivalent (SLE) between 1902 and 2009. Using projected temperature and precipitation anomalies from 15 coupled general circulation models from the Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble, they are projected to lose an additional 148 ± 35 mm SLE (scenario RCP26), 166 ± 42 mm SLE (scenario RCP45), 175 ± 40 mm SLE (scenario RCP60), or 217 ± 47 mm SLE (scenario RCP85) during the 21st century. Based on the extended RCP scenarios, glaciers are projected to approach a new equilibrium towards the end of the 23rd century, after having lost either 248 ± 66 mm SLE (scenario RCP26), 313 ± 50 mm SLE (scenario RCP45), or 424 ± 46 mm SLE (scenario RCP85). Up until approximately 2100, ensemble uncertainty within each scenario is the biggest source of uncertainty for the future glacier mass loss; after that, the difference between the scenarios takes over as the biggest source of uncertainty. Ice mass loss rates are projected to peak 2040 ∼ 2050 (RCP26), 2050 ∼ 2060 (RCP45), 2070 ∼ 2090 (RCP60), or 2070 ∼ 2100 (RCP85).
23
Charlton-Perez, A. J., E. Hawkins, V. Eyring, I. Cionni, G. E. Bodeker, D. E. Kinnison, H. Akiyoshi, et al. "Quantifying uncertainty in projections of stratospheric ozone over the 21st century." Atmospheric Chemistry and Physics Discussions 10, no. 5 (May 6, 2010): 11915–50. http://dx.doi.org/10.5194/acpd-10-11915-2010.
Abstract:
Abstract. Future stratospheric ozone concentrations will be determined both by changes in the concentration of ozone depleting substances (ODSs) and by changes in stratospheric and tropospheric climate, including those caused by changes in anthropogenic greenhouse gases (GHGs). Since future economic development pathways and resultant emissions of GHGs are uncertain, anthropogenic climate change could be a significant source of uncertainty for future projections of stratospheric ozone. In this pilot study, using an "ensemble of opportunity" of chemistry-climate model (CCM) simulations, the contribution of scenario uncertainty from different plausible emissions pathways for ODSs and GHGs to future ozone projections is quantified relative to the contribution from model uncertainty and internal variability of the chemistry-climate system. For both the global, annual mean ozone concentration and for ozone in specific geographical regions, differences between CCMs are the dominant source of uncertainty for the first two-thirds of the 21st century, up-to and after the time when ozone concentrations return to 1980 values. In the last third of the 21st century, dependent upon the set of greenhouse gas scenarios used, scenario uncertainty can be the dominant contributor. This result suggests that investment in chemistry-climate modelling is likely to continue to refine projections of stratospheric ozone and estimates of the return of stratospheric ozone concentrations to pre-1980 levels.
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Charlton-Perez, A. J., E. Hawkins, V. Eyring, I. Cionni, G. E. Bodeker, D. E. Kinnison, H. Akiyoshi, et al. "The potential to narrow uncertainty in projections of stratospheric ozone over the 21st century." Atmospheric Chemistry and Physics 10, no. 19 (October 7, 2010): 9473–86. http://dx.doi.org/10.5194/acp-10-9473-2010.
Abstract:
Abstract. Future stratospheric ozone concentrations will be determined both by changes in the concentration of ozone depleting substances (ODSs) and by changes in stratospheric and tropospheric climate, including those caused by changes in anthropogenic greenhouse gases (GHGs). Since future economic development pathways and resultant emissions of GHGs are uncertain, anthropogenic climate change could be a significant source of uncertainty for future projections of stratospheric ozone. In this pilot study, using an "ensemble of opportunity" of chemistry-climate model (CCM) simulations, the contribution of scenario uncertainty from different plausible emissions pathways for ODSs and GHGs to future ozone projections is quantified relative to the contribution from model uncertainty and internal variability of the chemistry-climate system. For both the global, annual mean ozone concentration and for ozone in specific geographical regions, differences between CCMs are the dominant source of uncertainty for the first two-thirds of the 21st century, up-to and after the time when ozone concentrations return to 1980 values. In the last third of the 21st century, dependent upon the set of greenhouse gas scenarios used, scenario uncertainty can be the dominant contributor. This result suggests that investment in chemistry-climate modelling is likely to continue to refine projections of stratospheric ozone and estimates of the return of stratospheric ozone concentrations to pre-1980 levels.
25
Beh, Eva H. Y., Holger R. Maier, and Graeme C. Dandy. "Scenario driven optimal sequencing under deep uncertainty." Environmental Modelling & Software 68 (June 2015): 181–95. http://dx.doi.org/10.1016/j.envsoft.2015.02.006.
26
Drouet, Laurent, and Johannes Emmerling. "Climate policy under socio-economic scenario uncertainty." Environmental Modelling & Software 79 (May 2016): 334–42. http://dx.doi.org/10.1016/j.envsoft.2016.02.010.
27
He, X., T. O. Sonnenborg, F. Jørgensen, A. S. Høyer, R. R. Møller, and K. H. Jensen. "Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time." Hydrology and Earth System Sciences 17, no. 8 (August 16, 2013): 3245–60. http://dx.doi.org/10.5194/hess-17-3245-2013.
Abstract:
Abstract. Uncertainty of groundwater model predictions has in the past mostly been related to uncertainty in the hydraulic parameters, whereas uncertainty in the geological structure has not been considered to the same extent. Recent developments in theoretical methods for quantifying geological uncertainty have made it possible to consider this factor in groundwater modeling. In this study we have applied the multiple-point geostatistical method (MPS) integrated in the Stanford Geostatistical Modeling Software (SGeMS) for exploring the impact of geological uncertainty on groundwater flow patterns for a site in Denmark. Realizations from the geostatistical model were used as input to a groundwater model developed from Modular three-dimensional finite-difference ground-water model (MODFLOW) within the Groundwater Modeling System (GMS) modeling environment. The uncertainty analysis was carried out in three scenarios involving simulation of groundwater head distribution and travel time. The first scenario implied 100 stochastic geological models all assigning the same hydraulic parameters for the same geological units. In the second scenario the same 100 geological models were subjected to model optimization, where the hydraulic parameters for each of them were estimated by calibration against observations of hydraulic head and stream discharge. In the third scenario each geological model was run with 216 randomized sets of parameters. The analysis documented that the uncertainty on the conceptual geological model was as significant as the uncertainty related to the embedded hydraulic parameters.
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He, X., T. O. Sonnenborg, F. Jørgensen, A. S. Høyer, R. Roende Møller, and K. H. Jensen. "Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time." Hydrology and Earth System Sciences Discussions 10, no. 3 (March 6, 2013): 2789–833. http://dx.doi.org/10.5194/hessd-10-2789-2013.
Abstract:
Abstract. Uncertainty of groundwater model predictions has in the past mostly been related to uncertainty in the hydraulic parameters whereas uncertainty in the geological structure has not been considered to the same extent. Recent developments in theoretical methods for quantifying geological uncertainty have made it possible to consider this factor in groundwater modeling. In this study we have applied the multiple-point geostatistical method (MPS) integrated in the Stanford Geostatistical Modeling Software (SGeMS) for exploring the impact of geological uncertainty on groundwater flow patterns for a site in Denmark. Realizations from the geostatistical model were used as input to a groundwater model developed from MODFLOW within the GMS modeling environment. The uncertainty analysis was carried out in three scenarios involving simulation of groundwater head distribution and groundwater age. The first scenario implied 100 stochastic geological models all assigning the same hydraulic parameters for the same geological units. In the second scenario the same 100 geological models were subjected to model optimization where the hydraulic parameters for each of them were estimated by calibration against observations of hydraulic head and stream discharge. In the third scenario each geological model was run with 216 randomized set of parameters. The analysis documented that the uncertainty on the conceptual geological model was as significant as the uncertainty related to the embedded hydraulic parameters.
29
Brodziak, Jon, and Kevin Piner. "Model averaging and probable status of North Pacific striped marlin, Tetrapturus audax." Canadian Journal of Fisheries and Aquatic Sciences 67, no. 5 (May 2010): 793–805. http://dx.doi.org/10.1139/f10-029.
Abstract:
We show how model averaging can be applied to estimate the probable status of a fishery resource under assessment scenario uncertainty. This approach is applied to North Pacific striped marlin ( Tetrapturus audax ), an apex predator that may be vulnerable to recruitment overfishing in pelagic longline fisheries targeting tunas. In the current striped marlin assessment, two assessment scenarios were used to account for different hypotheses about the steepness of the stock–recruitment dynamics. Estimates of spawning stock and recruitment from these scenarios are used post hoc to fit age-structured production models that represent alternative hypotheses about the degree of compensation in stock–recruitment dynamics and the degree of serial correlation of environmental forcing. Model-averaged estimates of target spawning biomass to produce maximum sustainable yield (SMSY) and the associated limit fishing mortality (FMSY) characterize relative stock status (S/SMSY and F/FMSY) under each scenario. Scenario-weighted averages of relative status determine probable stock status, with weightings reflecting the credibility of each scenario. Estimates of the variance of probable status account for both model selection and assessment scenario uncertainty in risk analyses. Using model averaging to estimate probable stock status from multiple assessment scenarios is analogous to using ensemble averages from multiple predictive models to make weather forecasts.
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Mustafa, Syed M. Touhidul, M. Moudud Hasan, Ajoy Kumar Saha, Rahena Parvin Rannu, Els Van Uytven, Patrick Willems, and Marijke Huysmans. "Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios." Hydrology and Earth System Sciences 23, no. 5 (May 13, 2019): 2279–303. http://dx.doi.org/10.5194/hess-23-2279-2019.
Abstract:
Abstract. Worldwide, groundwater resources are under a constant threat of overexploitation and pollution due to anthropogenic and climatic pressures. For sustainable management and policy making a reliable prediction of groundwater levels for different future scenarios is necessary. Uncertainties are present in these groundwater-level predictions and originate from greenhouse gas scenarios, climate models, conceptual hydro(geo)logical models (CHMs) and groundwater abstraction scenarios. The aim of this study is to quantify the individual uncertainty contributions using an ensemble of 2 greenhouse gas scenarios (representative concentration pathways 4.5 and 8.5), 22 global climate models, 15 alternative CHMs and 5 groundwater abstraction scenarios. This multi-model ensemble approach was applied to a drought-prone study area in Bangladesh. Findings of this study, firstly, point to the strong dependence of the groundwater levels on the CHMs considered. All groundwater abstraction scenarios showed a significant decrease in groundwater levels. If the current groundwater abstraction trend continues, the groundwater level is predicted to decline about 5 to 6 times faster for the future period 2026–2047 compared to the baseline period (1985–2006). Even with a 30 % lower groundwater abstraction rate, the mean monthly groundwater level would decrease by up to 14 m in the southwestern part of the study area. The groundwater abstraction in the northwestern part of Bangladesh has to decrease by 60 % of the current abstraction to ensure sustainable use of groundwater. Finally, the difference in abstraction scenarios was identified as the dominant uncertainty source. CHM uncertainty contributed about 23 % of total uncertainty. The alternative CHM uncertainty contribution is higher than the recharge scenario uncertainty contribution, including the greenhouse gas scenario and climate model uncertainty contributions. It is recommended that future groundwater-level prediction studies should use multi-model and multiple climate and abstraction scenarios.
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PSHENYCHNA, Iryna, Yuliia PRODIUS, and Serhii IZOTOV. "Scenario planning for the development of foreign economic activity of the hotel business enterprise in the conditions of the world pandemic." Economics. Finances. Law, no. 6 (June 18, 2021): 9–13. http://dx.doi.org/10.37634/efp.2021.6.2.
Abstract:
Introduction. The hotel business is traditionally considered a highly profitable area of foreign economic activity. The most significant risk factors are considered to be economic, political and social instability in countries and regions. In 2020, almost all global tourism and hotel businesses faced a serious challenge in their development – a severe crisis caused by the rapid spread of a pandemic of a new species of coronavirus (COVID-19) around the world. In the context of a global pandemic, to support the activities of the hotel business, it is necessary to clearly define the content and sequence of certain actions to achieve the goals, which determines the process of planning and forecasting the activities of the enterprise. Scenario planning is a fairly flexible process of describing possible future scenarios. This is part of strategic planning, which refers to the tools and technologies that manage future uncertainty. The purpose of the paper is to consider the scenario planning of the development of foreign economic activity of the hotel-type enterprise in conditions of economic uncertainty. The paper considers scenario planning as one of the most effective tools of strategic planning at the enterprise, which allows to forecast the development of events in the shortest possible time and update the planned indicators for its effective management. Results. In the course of this research the method of strategic planning is used – scenario planning, with the help of which all possible forecasts of events at the enterprise in crisis conditions are built. An analysis of hotel activities during the pandemic. The methods of scenario planning at the hotel business enterprise in the conditions of economic uncertainty are investigated. The difference between traditional and scenario approaches to strategic planning is clarified. Scenarios of possible events of the hotel business enterprise in the future in the conditions of a pandemic on the example of a scenario cross are developed. Conclusion. Scenario planning proved its effectiveness during the global pandemic, when hotel enterprises that applied scenario planning were ready for change and simply applied a different scenario, continuing to go with the flow. Scenarios for further development of foreign economic activity of the enterprise are determined.
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Ward, J. D., A. D. Werner, W. P. Nel, and S. Beecham. "The influence of constrained fossil fuel emissions scenarios on climate and water resource projections." Hydrology and Earth System Sciences 15, no. 6 (June 21, 2011): 1879–93. http://dx.doi.org/10.5194/hess-15-1879-2011.
Abstract:
Abstract. Water resources planning requires long-term projections of the impact of climate change on freshwater resources. In addition to intrinsic uncertainty associated with the natural climate, projections of climate change are subject to the combined uncertainties associated with selection of emissions scenarios, GCM ensembles and downscaling techniques. In particular, unknown future greenhouse gas emissions contribute substantially to the overall uncertainty. We contend that a reduction in uncertainty is possible by refining emissions scenarios. We present a comprehensive review of the growing body of literature that challenges the assumptions underlying the high-growth emissions scenarios (widely used in climate change impact studies), and instead points to a peak and decline in fossil fuel production occurring in the 21st century. We find that the IPCC's new RCP 4.5 scenario (low-medium emissions), as well as the B1 and A1T (low emissions) marker scenarios from the IPCC's Special Report on Emissions Scenarios are broadly consistent with the majority of recent fossil fuel production forecasts, whereas the medium to high emissions scenarios generally depend upon unrealistic assumptions of future fossil fuel production. We use a simple case study of projected climate change in 2070 for the Scott Creek catchment in South Australia to demonstrate that even with the current suite of climate models, by limiting projections to the B1 scenario, both the median change and the spread of model results are reduced relative to equivalent projections under an unrealistic high emissions scenario (A1FI).
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Ward, J. D., A. D. Werner, W. P. Nel, and S. Beecham. "The influence of constrained fossil fuel emissions scenarios on climate and water resource projections." Hydrology and Earth System Sciences Discussions 8, no. 2 (March 8, 2011): 2627–65. http://dx.doi.org/10.5194/hessd-8-2627-2011.
Abstract:
Abstract. Water resources planning requires long-term projections of the impact of climate change on freshwater resources. In addition to intrinsic uncertainty associated with the natural climate, projections of climate change are subject to the combined uncertainties associated with selection of emissions scenarios, GCM ensembles and downscaling techniques. In particular, unknown future greenhouse gas emissions contribute substantially to the overall uncertainty. We contend that a reduction in uncertainty is possible by refining emissions scenarios. We present a comprehensive review of the growing body of literature that challenges the assumptions underlying the high-growth emissions scenarios (widely used in climate change impact studies), and instead points to a peak and decline in fossil fuel production occurring in the 21st century. We find that the IPCC's new RCP 4.5 scenario (low-medium emissions), as well as the B1 and A1T (low emissions) marker scenarios from the IPCC's Special Report on Emissions Scenarios are broadly consistent with the majority of recent fossil fuel production forecasts, whereas the medium to high emissions scenarios generally depend upon unrealistic assumptions of future fossil fuel production. We use a simple case study of projected climate change in 2070 for the Scott Creek catchment in South Australia to demonstrate that even with the current suite of climate models, by limiting projections to the B1 scenario, both the median change and the spread of model results are reduced relative to equivalent projections under an unrealistic high emissions scenario (A1FI).
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Kolotaev, Y. Y. "Problems and Issues of Humanitarian Policy Representation in the Era of Digital Uncertainty." Governance and Politics 2, no. 4 (January 2, 2024): 53–67. http://dx.doi.org/10.24833/2782-7062-2023-2-4-53-67.
Abstract:
The article considers the problems of representation of the humanitarian policy achievements of the Russian Federation in contemporary fragmented information space conditions. Modern digital reality imposes multiple structural limitations on the objectives of the state’s humanitarian activities abroad, expressed in the problems of forming the country’s image through online platforms that actively hinder Russian soft power. The article aims to establish basic scenarios of response to the existing limitations in humanitarian policy representation. The methodological basis is scenario analysis with elements of agent-based modeling in describing the activities of digital platforms in the information moderation process. The paper explores the problems of terminological pluralism associated with “humanitarian policy,” as well as ideological and normative constraints imposed on Russian humanitarian activities. In addition, the paper describes the mechanisms of digital interference of online platforms in the information space and models three basic and one additional response scenario to such challenges. The basic scenarios include an alternative information space formation, convergence with the information space of other countries, and restoration of status in the global space. Each scenario has its own reputational and technical costs, partly addressed by the additional scenario based on less widespread but relatively independent information platforms. The main conclusion of this article is the need to develop a balanced approach within the framework of Russian humanitarian and information policy, taking into account the costs of all basic scenarios and relying on the current correlation between technical capabilities and defined objectives
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Choi, Yun, Kim, Jin, and Kim. "Robust Optimization Approach Using Scenario Concepts for Artillery Firing Scheduling Under Uncertainty." Applied Sciences 9, no. 14 (July 14, 2019): 2811. http://dx.doi.org/10.3390/app9142811.
Abstract:
Real wars involve a considerable number of uncertainties when determining firing scheduling. This study proposes a robust optimization model that considers uncertainties in wars. In this model, parameters that are affected by enemy’s behavior and will, i.e., threats from enemy targets and threat time from enemy targets, are assumed as uncertain parameters. The robust optimization model considering these parameters is an intractable model with semi-infinite constraints. Thus, this study proposes an approach to obtain a solution by reformulating this model into a tractable problem; the approach involves developing a robust optimization model using the scenario concept and finding a solution in that model. Here, the combinations that express uncertain parameters are assumed by scenarios. This approach divides problems into master and subproblems to find a robust solution. A genetic algorithm is utilized in the master problem to overcome the complexity of global searches, thereby obtaining a solution within a reasonable time. In the subproblem, the worst scenarios for any solution are searched to find the robust solution even in cases where all scenarios have been expressed. Numerical experiments are conducted to compare robust and nominal solutions for various uncertainty levels to verify the superiority of the robust solution.
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Chang, Yufang, Xinyi Zhou, Wencong Huang, and Guisheng Zhai. "Optimal scheduling of integrated energy systems considering wind power uncertainty." International Journal of Low-Carbon Technologies 19 (2024): 706–13. http://dx.doi.org/10.1093/ijlct/ctad149.
Abstract:
Abstract To reduce the impact of high wind power penetration rate on integrated energy systems, a wind power scenario generation method based on polynomial regression is proposed and an optimization scheduling model is constructed accordingly. First, a probability distribution model for wind power is constructed. Then, scenario generation is performed through Latin hypercube sampling and typical scenarios are obtained using the synchronous back propagation elimination method. Finally, the optimal output of each piece of equipment in the system is obtained with the lowest overall cost as the optimization objective. The simulation results validate the effectiveness and low-carbon nature of this method, while reducing costs.
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Harris, Gerald. "Four blind alleys of scenario analysis." Strategy & Leadership 42, no. 6 (November 11, 2014): 37–41. http://dx.doi.org/10.1108/sl-09-2014-0068.
Abstract:
Purpose – Some scenario projects, especially those that take short cuts, have design flaws that undermine the whole purpose of scenario analysis. This article aims to investigate these. Design/methodology/approach – This article is a guide to avoiding four common project flaws. Findings – Selecting one desired future and using scenario analysis to promote it to the exclusion of other possibilities is not a wise approach. Practical implications – Scenarios that ignore the likelihood of serious competition from fledgling startups, market invaders from other industries, or even the possibility of several companies combining to gain the competencies needed to be a threat, are not addressing the future’s full spectrum of competitive uncertainty. Originality/value – By becoming aware of the four “blind alleys” of scenario analysis warned about in this article, practitioners are more likely to use this planning tool effectively to scope out the true outlines of uncertainty or the fallout from discontinuity and prepare their firm to cope with new realities.
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Qian, Xinbo, Qiuhua Tang, and Bo Tao. "A Novel Scenario Reduction Method by 3D-Outputs Clustering for Condition-Based Maintenance Optimization." International Journal of Reliability, Quality and Safety Engineering 24, no. 04 (April 19, 2017): 1750018. http://dx.doi.org/10.1142/s0218539317500188.
Abstract:
Condition-based maintenance (CBM) optimization involves considering inherent uncertainties and external uncertainties. Since computational complexity increases exponentially with the number of degradation uncertainties and stages, scenario reduction aims to select small set of typical scenarios which can maintain the probability distributions of outputs of possible scenarios. A novel scenario reduction method, 3D-outputs-clustering scenario reduction (3DOCS), is presented by considering the impacts of uncertainty parameters on the output performance for CBM optimization which have been overlooked. Since the output performance for CBM is much more essential than the inputs, the proposed scenario reduction method reduces degradation scenarios by [Formula: see text]-means clustering of the multiple outputs of degradations scenarios for CBM. It minimizes the probabilistic distribution distances of outputs between original and selected scenarios. Case studies show that 3DOCS has advantages as a smaller distance of output performance of selected scenarios compared to that of initial scenarios.
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Keilman, Nico. "Uncertainty in Population Forecasts for the Twenty-First Century." Annual Review of Resource Economics 12, no. 1 (October 6, 2020): 449–70. http://dx.doi.org/10.1146/annurev-resource-110319-114841.
Abstract:
The aim of this article is to review a number of issues related to uncertain population forecasts, with a focus on world population. Why are these forecasts uncertain? Population forecasters traditionally follow two approaches when dealing with this uncertainty, namely scenarios (forecast variants) and probabilistic forecasts. Early probabilistic population forecast models were based upon a frequentist approach, whereas current ones are of the Bayesian type. I evaluate the scenario approach versus the probabilistic approach and conclude that the latter is preferred. Finally, forecasts of resources need not only population input, but also input on future numbers of households. While methods for computing probabilistic country-specific household forecasts have been known for some time, how to compute such forecasts for the whole world is yet an unexplored issue.
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Evin, Guillaume, Benoit Hingray, Juliette Blanchet, Nicolas Eckert, Samuel Morin, and Deborah Verfaillie. "Partitioning Uncertainty Components of an Incomplete Ensemble of Climate Projections Using Data Augmentation." Journal of Climate 32, no. 8 (April 12, 2019): 2423–40. http://dx.doi.org/10.1175/jcli-d-18-0606.1.
Abstract:
Abstract The quantification of uncertainty sources in ensembles of climate projections obtained from combinations of different scenarios and climate and impact models is a key issue in climate impact studies. The small size of the ensembles of simulation chains and their incomplete sampling of scenario and climate model combinations makes the analysis difficult. In the popular single-time ANOVA approach for instance, a precise estimate of internal variability requires multiple members for each simulation chain (e.g., each emission scenario–climate model combination), but multiple members are typically available for a few chains only. In most ensembles also, a precise partition of model uncertainty components is not possible because the matrix of available scenario/models combinations is incomplete (i.e., projections are missing for many scenario–model combinations). The method we present here, based on data augmentation and Bayesian techniques, overcomes such limitations and makes the statistical analysis possible for single-member and incomplete ensembles. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. This approach is illustrated for projections of regional precipitation and temperature for four mountain massifs in France. It is applicable for any kind of ensemble of climate projections, including those produced from ad hoc impact models.
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Wei, Wei, Li Ye, Yi Fang, Yingchun Wang, Xi Chen, and Zhenhua Li. "Optimal Allocation of Energy Storage Capacity in Microgrids Considering the Uncertainty of Renewable Energy Generation." Sustainability 15, no. 12 (June 14, 2023): 9544. http://dx.doi.org/10.3390/su15129544.
Abstract:
The high dimensionality and uncertainty of renewable energy generation restrict the ability of the microgrid to consume renewable energy. Therefore, it is necessary to fully consider the renewable energy generation of each day and time period in a long dispatching period during the deployment of energy storage in the microgrid. To this end, a typical multi-day scenario set is used as the simulation operation scenario, and an optimal allocation method of microgrid energy storage capacity considering the uncertainty of renewable energy generation is designed. Firstly, the historical scenarios are clustered into K types of daily state types using the K-means algorithm, and the corresponding probability distribution is obtained. Secondly, the Latin hypercube sampling method is used to obtain the state type of each day in a multi-day scenario set. Then, the daily scenario generation method based on conditional generative adversarial networks is used to generate a multi-day scenario set, combining the day state type as a condition, and then the typical scenario set is obtained using scenario reduction. Furthermore, a double-layer optimization allocation model for the energy storage capacity of microgrids is constructed, in which the upper layer optimizes the energy storage allocation capacity and the lower layer optimizes the operation plans of microgrids in each typical scenario. Finally, the proposed model is solved using the PSO algorithm nested with the CPLEX solver. In the microgrid example, the proposed method reduces the expected annual total cost by 19.66% compared with the stochastic optimal allocation method that assumes the scenic power obeys a specific distribution, proving that it can better cope with the uncertainty of renewable energy generation. At the same time, the expected annual total cost is reduced by 6.99% compared with the optimal allocation method that generates typical daily scenarios based on generative adversarial networks, which proves that it can better cope with the high dimensionality of renewable energy generation.
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Bégin, Jean-François. "ECONOMIC SCENARIO GENERATOR AND PARAMETER UNCERTAINTY: A BAYESIAN APPROACH." ASTIN Bulletin 49, no. 2 (April 14, 2019): 335–72. http://dx.doi.org/10.1017/asb.2019.6.
Abstract:
AbstractIn this article, we study parameter uncertainty and its actuarial implications in the context of economic scenario generators. To account for this additional source of uncertainty in a consistent manner, we cast Wilkie’s four-factor framework into a Bayesian model. The posterior distribution of the model parameters is estimated using Markov chain Monte Carlo methods and is used to perform Bayesian predictions on the future values of the inflation rate, the dividend yield, the dividend index return and the long-term interest rate. According to the US data, parameter uncertainty has a significant impact on the dispersion of the four economic variables of Wilkie’s framework. The impact of such parameter uncertainty is then assessed for a portfolio of annuities: the right tail of the loss distribution is significantly heavier when parameters are assumed random and when this uncertainty is estimated in a consistent manner. The risk measures on the loss variable computed with parameter uncertainty are at least 12% larger than their deterministic counterparts.
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Fricke, Christine. "The Uncertainty of Oil." TSANTSA – Journal of the Swiss Anthropological Association 22 (May 1, 2017): 28–36. http://dx.doi.org/10.36950/tsantsa.2017.22.7344.
Abstract:
This paper argues that uncertainty is intricately entwined with temporalities and aff ects. Taking the uncertain future of oil in Gabon as my ethnographic example, I trace fi ve versions with which people contemplate depletion: a scenario, a vision / plan, a calculation, a dream, and a desire. I show how these versions not only diff er in their prognosis, but also conjure up diverse histories, temporalities and aff ects that, ultimately, entail fairly distinct forms of uncertainty.
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Almendarez-Hernández, Luis César, Germán Ponce-Díaz, Daniel Lluch-Belda, Pablo Del Monte-Luna, and Romeo Saldívar-Lucio. "Risk assessment and uncertainty of the shrimp trawl fishery in the Gulf of California considering environmental variability." Latin American Journal of Aquatic Research 43, no. 4 (February 28, 2017): 651–61. http://dx.doi.org/10.3856/vol43-issue4-fulltext-4.
Abstract:
The shrimp fishery off the Mexican Pacific coast is the country's most important fishery from the economic standpoint. However, it faces serious problems, including the fleet’s overcapitalization and age, in addition to the environmental variability that affects the size of catches. Thus, this activity depends on a variety of factors that add uncertainty to the profitability of fishing vessels. This study aims to estimate the probability of success and economic risk of "type vessels" under two different environmental variability scenarios in the Gulf of California. The results from the economic simulation pointed to the vessel type used in Guaymas (Sonora) as the most efficient one under a neutral climate change scenario, showing a homogeneous behaviour in physical characteristics and mode of operation. By contrast, under a scenario of a monotonic rise in sea surface temperature, the shrimp fishery faces a greater risk of incurring economic losses. The simulated climate behaviour scenarios revealed that the activity involves a moderate economic profitability under the neutral scenario; however, under the warming scenario, profitability may be low or even nil due to the risks and uncertainty resulting from the influence of environmental phenomena.
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Oliver, John J., and Emma Parrett. "Managing uncertainty: harnessing the power of scenario planning." Strategic Direction 33, no. 1 (January 9, 2017): 5–6. http://dx.doi.org/10.1108/sd-09-2016-0131.
Abstract:
Purpose This paper aims to provide an overview of the role that scenario planning can play in managing the uncertainty caused by changing and unpredictable competitive dynamics. Design/methodology/approach This viewpoint reflects both the practical experience of strategic planners, combined with an academic insight into the advantages of using scenario planning as a management tool. Findings Firms can develop corporate level strategy and gain long-term certainty in their strategic approach by using scenario planning to strategize in a way that allows them to prepare for multiple futures, with multiple strategies. Practical implications Firms can manage environmental uncertainty and turbulence by being “mentally prepared” to address the future by evaluating the critical uncertainties driving turbulence and the strategic options relevant to a number of possible future outcomes. Originality/value A unique combination of practical experience fused with academic knowledge on harnessing the power of scenario planning to manage uncertainty and develop organizational strategy.
46
Zheng, Xiao Li, Ji Chun Liu, Jia Yi Li, Yun Xia Wu, Fang Zhang, Hong Hui Chen, Xiang Yang An, and Chen He. "The Reserve Capacity Model Based on the Idea of Scenario in Power System." Advanced Materials Research 1008-1009 (August 2014): 173–78. http://dx.doi.org/10.4028/www.scientific.net/amr.1008-1009.173.
Abstract:
According to the impact of the wind power prediction uncertainty on the power system reserve capacity, the idea of scenario is introduced to the stochastic programming model. The method of scenario is used to simulate the uncertainty model of the wind power generation, load and the conventional units. The scenario-reduction methodology is combined to reduce the large scenario set to a simpler one, then the probability statistics on these scenarios is given in order to obtain the probability density of the system power difference, and the expected energy not supplied (EENS) and expected wind waste risk (EWWR) are presented. The reserve capacity is determined by the two aspects, which are the reliability shown by EENS and EWWR, and the economy of reserve capacity cost. Finally, simulations on a ten-unit system are given to demonstrate the method is effective to reduce the cost of reserve and the abandoned wind power in the context of system reliability.
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Prato, Tony. "Conceptual Framework for Collaboratively Managing Coupled Human and Natural Systems under Climate Change Uncertainty." Environment and Natural Resources Research 6, no. 1 (December 21, 2015): 13. http://dx.doi.org/10.5539/enrr.v6n1p13.
Abstract:
<p class="1Body">A collaborative decision making (CDM) framework is developed for managing coupled human and natural systems (CHANS) over time when managers are uncertain about one or more drivers of system behavior. The framework incorporates six elements: (1) framing the problem; (2) selecting management objectives; (3) choosing scenarios for future changes in one or more drivers of system behavior; (4) formulating alternative management actions; (5) estimating the values of management objectives and determining their compliance with maximum or minimum acceptable levels; and (6) determining preferred management actions for each driver scenario and time period. Application of the framework is illustrated for a hypothetical case study that determines preferred management actions over time for a highway corridor through a hypothetical national park based on four management objectives: minimizing soil erosion and vegetative losses along hiking trails in the highway corridor; and minimizing traffic congestion on the highway and visitor congestion on hiking trails in the highway corridor. Uncertainty about future visitor use of the highway corridor is taken into account by specifying low, medium, and high visitor use scenarios for the corridor. Preferred management actions for each visitor use scenario within time periods are determined using the fuzzy Technique for Order Preference by Similarity of Ideal Solution to rank management actions for each visitor use scenario. The preferred management action across visitor use scenarios for each time period is determined by applying the minimax regret criterion to maximum loss indices for the preferred management actions for visitor use scenarios.</p>
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Bamber, Jonathan L., Michael Oppenheimer, Robert E. Kopp, Willy P. Aspinall, and Roger M. Cooke. "Ice sheet contributions to future sea-level rise from structured expert judgment." Proceedings of the National Academy of Sciences 116, no. 23 (May 20, 2019): 11195–200. http://dx.doi.org/10.1073/pnas.1817205116.
Abstract:
Despite considerable advances in process understanding, numerical modeling, and the observational record of ice sheet contributions to global mean sea-level rise (SLR) since the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, severe limitations remain in the predictive capability of ice sheet models. As a consequence, the potential contributions of ice sheets remain the largest source of uncertainty in projecting future SLR. Here, we report the findings of a structured expert judgement study, using unique techniques for modeling correlations between inter- and intra-ice sheet processes and their tail dependences. We find that since the AR5, expert uncertainty has grown, in particular because of uncertain ice dynamic effects. For a +2 °C temperature scenario consistent with the Paris Agreement, we obtain a median estimate of a 26 cm SLR contribution by 2100, with a 95th percentile value of 81 cm. For a +5 °C temperature scenario more consistent with unchecked emissions growth, the corresponding values are 51 and 178 cm, respectively. Inclusion of thermal expansion and glacier contributions results in a global total SLR estimate that exceeds 2 m at the 95th percentile. Our findings support the use of scenarios of 21st century global total SLR exceeding 2 m for planning purposes. Beyond 2100, uncertainty and projected SLR increase rapidly. The 95th percentile ice sheet contribution by 2200, for the +5 °C scenario, is 7.5 m as a result of instabilities coming into play in both West and East Antarctica. Introducing process correlations and tail dependences increases estimates by roughly 15%.
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Kwon, Soon Ho, Donghwi Jung, and Joong Hoon Kim. "Development of a Multiscenario Planning Approach for Urban Drainage Systems." Applied Sciences 10, no. 5 (March 6, 2020): 1834. http://dx.doi.org/10.3390/app10051834.
Abstract:
A traditional urban drainage system (UDS) planning approach generally considers the most probable future rainfall scenario. However, this single scenario (i.e., scenario-optimal) planning approach is prone to failure under recent climatic conditions, which involve increasing levels of uncertainty. To overcome this limitation, an alternative is to consider multiple scenarios simultaneously. A two-phase multi-scenario-based UDS planning approach was developed. Scenario-optimal solutions were determined for a set of scenarios in Phase I, as the traditional planning approach, while common elements across the scenarios were identified and used to consider components-wise regret cost concept for Phase II optimization, from which a compromise solution was sought. The storm water management model was dynamically linked with the harmony search algorithm for each phase optimization model. The proposed approach was demonstrated in the planning of the grid-type drainage networks of S-city. The compromise solution was compared with the scenario-optimal solutions (Phase I) with respect to cost effectiveness and system performance under scenarios that were not considered in the planning phase.
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Cameron, D., K. Beven, and P. Naden. "Flood frequency estimation by continuous simulation under climate change (with uncertainty)." Hydrology and Earth System Sciences 4, no. 3 (September 30, 2000): 393–405. http://dx.doi.org/10.5194/hess-4-393-2000.
Abstract:
Abstract. This paper explores the potential for assessing the impacts of climate change upon flood frequency for the gauged, upland Wye catchment at Plynlimon, Wales, UK, while taking account of uncertainty in modelling rainfall-runoff processes under current conditions. A continuous simulation methodology which uses a stochastic rainfall model to drive the rainfall-runoff model TOPMODEL is utilised. Behavioural parameter sets for both the rainfall model and TOPMODEL are identified prior to the climate change runs using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The "medium-high" UKCIP98 climate change scenario, obtained from the HadCM2 GCM simulations, is used as a starting point for a variety of different scenarios at the catchment scale. It is demonstrated that while the scenarios have only a small impact upon the likelihood weighted flood frequency uncertainty bounds in comparison with the current condition scenario, the risk of a given discharge as an element in the distribution of T year floods is changed. This underlines the need to account explicitly for uncertainty within hydrological modelling, especially in estimating the impacts of climate change. Keywords: Climate change; Floods; Frequency; TOPMODEL