Physical Sciences and Mathematics Commons^™

Adoption Of Switchgrass Cultivation For Biofuel Under Uncertainty: A Discrete-Time Modeling Approach, Pralhad Burli, Eric Forgoston, Pankaj Lal, Lora Billings, Bernabas Wolde

Lora Billings

Adoption Of Switchgrass Cultivation For Biofuel Under Uncertainty: A Discrete-Time Modeling Approach, Pralhad Burli, Eric Forgoston, Pankaj Lal, Lora Billings, Bernabas Wolde

Eric Forgoston

Adoption Of Switchgrass Cultivation For Biofuel Under Uncertainty: A Discrete-Time Modeling Approach, Pralhad Burli, Eric Forgoston, Pankaj Lal, Lora Billings, Bernabas Wolde

Pankaj Lal

Towards Mapping Soil Carbon Landscapes: Issues Of Sampling Scale And Transferability, Bradley A. Miller, Sylvia Koszinski, Wilfried Hierold, Helmut Rogasik, Boris Schröder, Kristof Van Oost, Marc Wehrhan, Michael Sommer

Bradley A Miller

The conversion of point observations to a geographic field is a necessary step in soil mapping. For pursuing goals of mapping soil carbon at the landscape scale, the relationships between sampling scale, representation of spatial variation, and accuracy of estimated error need to be considered. This study examines the spatial patterns and accuracy of predictions made by different spatial modelling methods on sample sets taken at two different scales. These spatial models are then tested on independent validation sets taken at three different scales. Each spatial modelling method produced similar, but unique, maps of soil organic carbon content (SOC%). Kriging …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen CHENG

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Global Patterns And Controls Of Soil Organic Carbon Dynamics As Simulated By Multiple Terrestrial Biosphere Models: Current Status And Future Directions, Hanqin Tian, Chaoqun (Crystal) Lu, Jia Yang, Kamaljit Banger, Denorah N. Huntzinger, Christopher R. Schwalm, Anna M. Michalak, Robert Cook, Philippe Ciais, Daniel Hayes, Maoyi Huang, Akihiko Ito, Atul K. Jain, Huimin Lei, Jiafu Mao, Shufen Pan, Wilfred M. Post, Shushi Peng, Benjamin Poulter, Wei Ren, Daniel Ricciuto, Kevin Schaefer, Xiaoying Shi, Bo Tao, Weile Wang, Yaxing Wei, Qichun Yang, Bowen Zhang, Ning Zeng

Chaoqun (Crystal) Lu

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO2) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long …

Fuzzy Mathematical Models Of Type-1 And Type-2 For Computing The Parameters And Its Applications, R.W. W. Hndoosh

R. W. Hndoosh

This work provides mathematical formulas and algorithm in order to calculate the derivatives that being necessary to perform Steepest Descent models to make T1 and T2 FLSs much more accessible to FLS modelers. It provides derivative computations that are applied on different kind of MFs, and some computations which are then clarified for specific MFs. We have learned how to model T1 FLSs when a set of training data is available and provided an application to derive the Steepest Descent models that depend on trigonometric function (SDTFM). This work, also focused on an interval type-2 non-singleton type-2 FLS (IT2 NS-T2 …

Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy Varakantham, Shih-Fen Cheng, Thi Duong Nguyen

Shih-Fen CHENG

This research is motivated by problems in urban transportation and labor mobility, where the agent flow is dynamic, non-deterministic and on a large scale. In such domains, even though the individual agents do not have an identity of their own and do not explicitly impact other agents, they have implicit interactions with other agents. While there has been much research in handling such implicit effects, it has primarily assumed controlled movements of agents in static environments. We address the issue of decision support for individual agents having involuntary movements in dynamic environments . For instance, in a taxi fleet serving …

Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen CHENG

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments, we show that under stochastic conditions the performance variation of the process decreases as the time frame length (time …

Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh

Shih-Fen CHENG

On May 6, 2010, the U.S. equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (see Figure 1) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. The authors contend that the events of May 6, 2010 exhibit patterns consistent with the type of "flash crash" observed in their earlier study (2010). This paper describes the results of nine different simulations created by using a large-scale computer model to reconstruct the critical elements …

Analysis Of Uncertain Data: Evaluation Of Given Hypotheses, Anatole Gershman, Eugene Fink, Bin Fu, Jaime G. Carbonell

Jaime G. Carbonell

We consider the problem of heuristic evaluation of given hypotheses based on limited observations, in situations when available data are insufficient for rigorous statistical analysis.

Confronting Socially Generated Uncertainty In Adaptive Management, Andrew J. Tyre, Sarah Michaels

Andrew J Tyre

As more and more organizations with responsibility for natural resource management adopt adaptive management as the rubric in which they wish to operate, it becomes increasingly important to consider the sources of uncertainty inherent in their endeavors. Without recognizing that uncertainty originates both in the natural world and in human undertakings, efforts to manage adaptively at the least will prove frustrating and at the worst will prove damaging to the very natural resources that are the management targets. There will be more surprises and those surprises potentially may prove at the very least unwanted and at the worst devastating. We …

Evaluating The Efficacy Of Adaptive Management Approaches: Is There A Formula For Success?, Jamie E. Mcfadden, Tim L. Hiller, Andrew J. Tyre

Andrew J Tyre

Within the field of natural-resources management, the application of adaptive management is appropriate for complex problems high in uncertainty. Adaptive management is becoming an increasingly popular management-decision tool within the scientific community and has developed into two primary schools of thought: the Resilience-Experimentalist School (with high emphasis on stakeholder involvement, resilience, and highly complex models) and the Decision-Theoretic School (which results in relatively simple models through emphasizing stakeholder involvement for identifying management objectives). Because of these differences, adaptive management plans implemented under each of these schools may yield varying levels of success. We evaluated peer-reviewed literature focused on incorporation of …

Small Town Water Governance In Developing Countries: The Uncertainty Curse, Magnus Moglia, Pascal Perez, Stewart Burn

Professor Pascal Perez

lack of consideration of local circumstances and process requirements, and in particular inadequate involvement of affected stakeholders as well as inadequate cross-sectorial coordination. This is not surprising given poor organizational memory combined with decisions being made under time pressure and strict deadlines combined with little adaptive capacity. Additionally, information about the importance of process requirements and engagement is qualitative and as such is unfortunately often given secondary importance. To address this, we suggest a Risk assessment component as part of the project design phase based on Bayesian Networks (BNs) utilizing expert and local knowledge. This not only improves organizational memory …

Accounting For Uncertainty In Ecological Analysis: The Strengths And Limitations Of Hierarchical Statistical Modeling, Noel Cressie, Catherine Calder, James Clark, Jay Ver Hoef, Christopher Wikle

Professor Noel Cressie

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple …

Climate Policy Under Uncertainty: A Case For Solar Geoengineering, Juan B. Moreno-Cruz, David W. Keith

Juan B. Moreno-Cruz

It appears to be technically feasible to engineer an increase in albedo, a planetary brightening, as a means to offset the warming caused by carbon dioxide (CO2) and other greenhouse gases through Solar Radiation Management (SRM). This option has two characteristics that make it attractive for managing climate risk: it is quick and cheap. However, SRM cannot exactly compensate for the CO2-driven climate change. Moreover, SRM introduces risks in the climate system that are unique to this type of intervention.We introduce SRM in a model of climate change economics and analyze the optimal policy under uncertainty. We find that the …

Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study, Ole J. Mengshoel, Mark Chavira, Keith Cascio, Adnan Darwiche, Scott Poll, Serdar Uckun

Ole J Mengshoel

We present in this paper a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system (EPS), i.e., the Advanced Diagnstic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. Our probabilistic approach is formally well founded and based on Bayesian networks (BNs) and arithmetic circuits (ACs). We pay special attention to meeting two of the main challenges often associated with real-world application of model-based diagnosis technologies: model development and real-time reasoning. To address the challenge of model development, we develop a systematic approach to representing EPSs as BNs, …

Algorithms For Distributed Chemical Sensor Fusion, Randy Paffenroth, Scott Lundberg, Jason Yosinski

Randy C. Paffenroth

No abstract provided.

Additivity Of Information Value In Two-Act Linear Loss Decisions With Normal Priors, Jeffrey Keisler

Jeffrey Keisler

For the two-act linear loss decision problem with normal priors, conditions are derived for which the expected value of perfect information about two independent risks is super-additive in value. Several applications show how a variety of decision problems can reduce to the canonical problem, and how the general results obtained here can be translated simply to prescriptions for specific situations.