Bibliographies thématiques / Elicitation of expert belief

Littérature scientifique sur le sujet « Elicitation of expert belief »

Auteur : Grafiati

Publié le 10 mars 2023

Mis à jour le 11 mars 2023

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Articles de revues sur le sujet "Elicitation of expert belief"

RENOOIJ, SILJA. « Probability elicitation for belief networks : issues to consider ». Knowledge Engineering Review 16, n^o 3 (septembre 2001) : 255–69. http://dx.doi.org/10.1017/s0269888901000145.

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Upon assessing probabilities for Bayesian belief networks, the knowledge and practical experience of experts is often the only available source of probabilistic information. It is important to realise that issues concerning human capabilities with respect to making judgements come into play when relying on experts for probability elicitation. A number of methods for the elicitation of probabilities are known from the field of decision analysis. These methods try, to some extent, to deal with those issues. I present here an overview of the issues to consider when relying on expert judgements and describe the methods that are available for expert elicitation, along with their benefits and drawbacks.

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Phillipson, Frank, Peter Langenkamp et Reinder Wolthuis. « Alternative Initial Probability Tables for Elicitation of Bayesian Belief Networks ». Mathematical and Computational Applications 26, n^o 3 (28 juillet 2021) : 54. http://dx.doi.org/10.3390/mca26030054.

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Bayesian Belief Networks are used in many fields of application. Defining the conditional dependencies via conditional probability tables requires the elicitation of expert belief to fill these tables, which grow very large quickly. In this work, we propose two methods to prepare these tables based on a low number of input parameters using specific structures and one method to generate the table using probability tables of each relation of a child node with a certain parent. These tables can be used further as a starting point for elicitation.

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COUPÉ, VEERLE M. H., LINDA C. VAN DER GAAG et J. DIK F. HABBEMA. « Sensitivity analysis : an aid for belief-network quantification ». Knowledge Engineering Review 15, n^o 3 (septembre 2000) : 215–32. http://dx.doi.org/10.1017/s0269888900003027.

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When building a Bayesian belief network, usually a large number of probabilities have to be assessed by experts in the domain of application. Experience shows that experts are often reluctant to assess all probabilities required, feeling that they are unable to give assessments with a high level of accuracy. We argue that the elicitation of probabilities from experts can be supported to a large extent by iteratively performing sensitivity analyses of the belief network in the making, starting with rough, initial assessments. Since it gives insight into which probabilities require a high level of accuracy and which do not, performing a sensitivity analysis allows for focusing further elicitation efforts. We propose an elicitation procedure in which, alternately, sensitivity analyses are performed and probability assessments refined, until satisfactory behaviour of the belief network is obtained, until the costs of further elicitation outweigh the benefits of higher accuracy or until higher accuracy can no longer be attained due to lack of knowledge.

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Bojke, Laura, Marta Soares, Karl Claxton, Abigail Colson, Aimée Fox, Christopher Jackson, Dina Jankovic, Alec Morton, Linda Sharples et Andrea Taylor. « Developing a reference protocol for structured expert elicitation in health-care decision-making : a mixed-methods study ». Health Technology Assessment 25, n^o 37 (juin 2021) : 1–124. http://dx.doi.org/10.3310/hta25370.

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Background Many decisions in health care aim to maximise health, requiring judgements about interventions that may have higher health effects but potentially incur additional costs (cost-effectiveness framework). The evidence used to establish cost-effectiveness is typically uncertain and it is important that this uncertainty is characterised. In situations in which evidence is uncertain, the experience of experts is essential. The process by which the beliefs of experts can be formally collected in a quantitative manner is structured expert elicitation. There is heterogeneity in the existing methodology used in health-care decision-making. A number of guidelines are available for structured expert elicitation; however, it is not clear if any of these are appropriate for health-care decision-making. Objectives The overall aim was to establish a protocol for structured expert elicitation to inform health-care decision-making. The objectives are to (1) provide clarity on methods for collecting and using experts’ judgements, (2) consider when alternative methodology may be required in particular contexts, (3) establish preferred approaches for elicitation on a range of parameters, (4) determine which elicitation methods allow experts to express uncertainty and (5) determine the usefulness of the reference protocol developed. Methods A mixed-methods approach was used: systemic review, targeted searches, experimental work and narrative synthesis. A review of the existing guidelines for structured expert elicitation was conducted. This identified the approaches used in existing guidelines (the ‘choices’) and determined if dominant approaches exist. Targeted review searches were conducted for selection of experts, level of elicitation, fitting and aggregation, assessing accuracy of judgements and heuristics and biases. To sift through the available choices, a set of principles that underpin the use of structured expert elicitation in health-care decision-making was defined using evidence generated from the targeted searches, quantities to elicit experimental evidence and consideration of constraints in health-care decision-making. These principles, including fitness for purpose and reflecting individual expert uncertainty, were applied to the set of choices to establish a reference protocol. An applied evaluation of the developed reference protocol was also undertaken. Results For many elements of structured expert elicitation, there was a lack of consistency across the existing guidelines. In almost all choices, there was a lack of empirical evidence supporting recommendations, and in some circumstances the principles are unable to provide sufficient justification for discounting particular choices. It is possible to define reference methods for health technology assessment. These include a focus on gathering experts with substantive skills, eliciting observable quantities and individual elicitation of beliefs. Additional considerations are required for decision-makers outside health technology assessment, for example at a local level, or for early technologies. Access to experts may be limited and in some circumstances group discussion may be needed to generate a distribution. Limitations The major limitation of the work conducted here lies not in the methods employed in the current work but in the evidence available from the wider literature relating to how appropriate particular methodological choices are. Conclusions The reference protocol is flexible in many choices. This may be a useful characteristic, as it is possible to apply this reference protocol across different settings. Further applied studies, which use the choices specified in this reference protocol, are required. Funding This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 37. See the NIHR Journals Library website for further project information. This work was also funded by the Medical Research Council (reference MR/N028511/1).

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Kreinovich, Vladik. « INTERVAL METHODS IN KNOWLEDGE REPRESENTATION ». International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 04, n^o 05 (octobre 1996) : 467–90. http://dx.doi.org/10.1142/s0218488596000433.

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In this issues, we continue to publish abstracts and reviews of recents papers on interval methods in knowledge representation. In knowledge representation, intervals are used for two main purposes: • to describe durations of events; and • to describe uncertainty of measurement results and expert estimates of different quantities; often, we do not know the exact value of a quantity, but we know its lower and upper bounds (e.g., we may not know the exact value of someone's weight, but we may know that this weight is in between 140 and 160 pounds). An important case of this uncertainty occurs in knowledge elicitation, when we ask experts to numerically estimate their degrees of belief in their own statements; in this case, it is often difficult for an expert to estimate this degree of belief precisely, but an expert can often provide us with an interval of possible values. The reviews are collected by Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA, email vladik@cs.utep.edu

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Anuar, Nadia, Ahmad Mazli Muhammad et Zainudin Awang. « An Exploratory Factor Analysis of Elicited Students’ Salient Beliefs Toward Critical Reading ». International Journal of Modern Languages And Applied Linguistics 4, n^o 4 (18 décembre 2020) : 101. http://dx.doi.org/10.24191/ijmal.v4i4.11288.

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Critical reading was named a key aspiration in the Malaysian Education Blueprint (2015-2025) and is an essential skill students must acquire. However, an increased number of students was reported to demonstrate poor critical reading performance at the workplace. Thus, Theory of Planned Behaviour (TPB) was utilised to examine students’ beliefs critical reading which encompass behavioural belief (advantages and disadvantages of critical reading), normative belief (identification of people who approve participating in critical reading), and control belief (difficulties in critical reading). A three-stage research design was employed. The first stage, elicitation study, was conducted as this stage has received minimum scholarly attention in the TPB literature and to ensure a more comprehensive analysis. The beliefs were analysed qualitatively, which was proceeded by expert panel review. Subsequently, exploratory factor analysis was conducted to determine the validity of the salient beliefs. Findings from the exploratory factor analysis and reliability analysis revealed that beliefs that were elicited from students in this first stage are appropriate and possess sufficient reliability and construct validity. Hence, the results of this study not only contributed to the critical reading and Theory of Planned Behaviour’s literature but have also identified more relevant factors that influence students’ perception toward critical reading.

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Carvalho, Arthur. « A Note on Sandroni-Shmaya Belief Elicitation Mechanism ». Journal of Prediction Markets 10, n^o 2 (27 janvier 2017) : 14–21. http://dx.doi.org/10.5750/jpm.v10i2.1225.

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Incentive-compatible methods for eliciting beliefs, such as proper scoring rules, often rely on strong assumptions about how humans behave when making decisions under risk and uncertainty. For example, standard proper scoring rules assume that humans are risk neutral, an assumption that is often violated in practice. Under such an assumption, proper scoring rules induce honest reporting of beliefs, in a sense that experts maximize their expected scores from a proper scoring rule by honestly reporting their beliefs.Sandroni and Shmaya [Economic Theory Bulletin, volume 1, issue 1, 2013] suggested a remarkable mechanism based on proper scoring rules that induces honest reporting of beliefs without any assumptions on experts’ risk attitudes. In particular, the authors claimed that the mechanism relies only on the natural assumptions of probabilistic sophistication and dominance. We suggest in this paper that the reduction of compound lotteries axiom is another assumption required for Sandroni and Shmaya’s mechanism to induce honest reporting of beliefs. We further elaborate on the implications of such an extra assumption in light of recent findings regarding the reduction of compound lotteries axiom.

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Bryant, Andrew, Michael Grayling, Shaun Hiu, Ketankumar Gajjar, Eugenie Johnson, Ahmed Elattar, Luke Vale, Dawn Craig et Raj Naik. « Residual disease after primary surgery for advanced epithelial ovarian cancer : expert elicitation exercise to explore opinions about potential impact of publication bias in a planned systematic review and meta-analysis ». BMJ Open 12, n^o 8 (août 2022) : e060183. http://dx.doi.org/10.1136/bmjopen-2021-060183.

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ObjectivesWe consider expert opinion and its incorporation into a planned meta-analysis as a way of adjusting for anticipated publication bias. We conduct an elicitation exercise among eligible British Gynaecological Cancer Society (BGCS) members with expertise in gynaecology.DesignExpert elicitation exercise.SettingBGCS.ParticipantsMembers of the BGCS with expertise in gynaecology.MethodsExperts were presented with details of a planned prospective systematic review and meta-analysis, assessing overall survival for the extent of excision of residual disease (RD) after primary surgery for advanced epithelial ovarian cancer. Participants were asked views on the likelihood of different studies (varied in the size of the study population and the RD thresholds being compared) not being published. Descriptive statistics were produced and opinions on total number of missing studies by sample size and magnitude of effect size estimated.ResultsEighteen expert respondents were included. Responders perceived publication bias to be a possibility for comparisons of RD <1 cm versus RD=0 cm, but more so for comparisons involving higher volume suboptimal RD thresholds. However, experts’ perceived publication bias in comparisons of RD=0 cm versus suboptimal RD thresholds did not translate into many elicited missing studies in Part B of the elicitation exercise. The median number of missing studies estimated by responders for the main comparison of RD<1 cm versus RD=0 cm was 10 (IQR: 5–20), with the number of missing studies influenced by whether the effect size was equivocal. The median number of missing studies estimated for suboptimal RD versus RD=0 cm was lower.ConclusionsThe results may raise awareness that a degree of scepticism is needed when reviewing studies comparing RD <1 cm versus RD=0 cm. There is also a belief among respondents that comparisons involving RD=0 cm and suboptimal thresholds (>1 cm) are likely to be impacted by publication bias, but this is unlikely to attenuate effect estimates in meta-analyses.

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Vijayan, Vimal, Sanjay K. Chaturvedi et Ritesh Chandra. « A failure interaction model for multicomponent repairable systems ». Proceedings of the Institution of Mechanical Engineers, Part O : Journal of Risk and Reliability 234, n^o 3 (3 février 2020) : 470–86. http://dx.doi.org/10.1177/1748006x19897828.

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Modeling of stochastic dependency among components in a repairable system is still a challenging task when dealing with the maintenance of multicomponent systems. With the help of stochastic dependency information, failure of a component brings attention to the components having strong interactions with the failed component. With this information, one can plan the maintenance of components in a better way. Since a change in failure probability of a component (due to deterioration or failure of a component in a given time interval) influences the failure probabilities of other components in the system, therefore, in this article, we consider probability of failure to represent the state of the component to model the stochastic dependency among components. We apply the Bayesian belief network to model such scenario of dependency among the components and present two case studies to compute various probabilities. In the first study, expert elicitation is being used, whereas the time between failure of the components is used in the second case to calculate failure probabilities. To illustrate the applicability of the proposed approach, one case study for each is presented. The first case study takes the case of an army truck through expert elicitation approach whereas the second case study deals with a rolling mill gearbox whose time between failure of components was available.

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Schlag, Karl H., et Joël J. van der Weele. « A method to elicit beliefs as most likely intervals ». Judgment and Decision Making 10, n^o 5 (septembre 2015) : 456–68. http://dx.doi.org/10.1017/s1930297500005593.

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AbstractWe show how to elicit the beliefs of an expert in the form of a “most likely interval”, a set of future outcomes that are deemed more likely than any other outcome. Our method, called the Most Likely Interval elicitation rule (MLI), asks the expert for an interval and pays according to how well the answer compares to the actual outcome. We show that the MLI performs well in economic experiments, and satisfies a number of desirable theoretical properties such as robustness to the risk preferences of the expert.

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Thèses sur le sujet "Elicitation of expert belief"

Briggs, Rachael (Rachael Amy). « Partial belief and expert testimony ». Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/47829.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2009.
Includes bibliographical references (p. [83]-86).
My dissertation investigates two questions from within a partial belief framework: First, when and how should deference to experts or other information sources be qualified? Second, how closely is epistemology related to other philosophical fields, such as metaphysics, ethics, and decision theory? Chapter 1 discusses David Lewis's "Big Bad Bug", an argument for the conclusion that the Principal Principle-the thesis that one's credence in a proposition A should equal one's expectation of A's chance, provided one has no inadmissible information-is incompatible with Humean Supervenience-the thesis that that laws of nature, dispositions, and objective chances supervene on the distribution of categorical properties in the world (past, present, and future). I map out the logical structure of the Big Bad Bug, survey a range of possible responses to it, and argue that none of the responses are very appealing. Chapter 2 discusses Bas van Fraassen's Reflection principle-the thesis that one's current credence in a proposition A should equal one's expected future credence in A. Van Fraassen has formulated a diachronic Dutch book argument for Reflection, but other authors cite counterexamples to Reflection that appear to undermine the credibility of diachronic Dutch books. I argue that a suitably qualified version of Reflection gets around the counterexamples. I distinguish between Dutch books that reveal incoherence-like the diachronic Dutch book for conditionalization-and Dutch books that reveal a type of problem I call selfdoubt. I argue that violating Reflection is a type of self-doubt rather than a type of incoherence.
(cont.) Chapter 3 argues that the halfer and thirder solutions to Adam Elga's Sleeping Beauty problem correspond to two more general approaches to de se information. Which approach is right depends on which approach to decision theory is right. I use Dutch books and scoring rules to argue that causal decision theorists should favor the approach that corresponds to thirding, while evidential decision theorists should favor the approach that corresponds to halfing.
by Rachael Briggs.
Ph.D.

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Selvidge, Jordan R. « Managing One-to-One Initiatives : Implementation Analysis Through Expert Elicitation ». Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3143.

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A qualitative phenomenological study was conducted to identify and analyze issues in the implementation of one-to-one computing initiatives and provide solutions for improvement. An understanding of the implementation process was developed through the analysis of data collected through 27 interviews with teacher experts in the field who have worked with the implementation of one-to-one programs. Teachers were purposely selected from the following groups: those who were completing their first year of teaching, those who had between two and ten years of teaching experience, and those who had eleven plus years of total teaching experience. This study distinctly addresses one-to-one initiatives from both placing importance on the utilization of negative knowledge and in simultaneously treating teacher perceptions as a valid reality. Issues associated with the implementation of one-to-one initiatives develop at a faster speed than traditional school structures are accustomed to respond to. Successful one-to-one management requires a responsive, interconnected, and efficient organizational structure. This research has significance for the improvement of one-to-one initiative implementation efforts. The findings contained in this research have the potential to benefit teachers, administrators, and other stakeholders associated with the implementation of one-to-one initiatives.

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Schneider, Mark. « Studies in risk perception and financial literacy : applications using subjective belief elicitation ». Doctoral thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/30349.

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The concept of literacy has grown from “reading literacy” to now encompass many different domain-specific topics and skill sets, such as health literacy, financial literacy, and computer literacy. The way literacy is talked about, examined, measured, and communicated has also evolved. Literacy measures began as a simple metric of counting the number of individuals in a country that could read and dividing that count by the total population to compute the percentage of literate individuals. However, this approach ignores situations in which an illiterate person has access to a literate person that could read to them. This was the premise of research in development economics that introduced the measure of effective literacy, which accounts for potential positive externalities that could arise from access to a literate individual. This dissertation expands on the idea of effective literacy and introduces a concept of extended literacy, which applies to a decision-maker having access to an external scaffold during the decision-making process. The scaffolds considered include access to the internet, to an anonymous person as part of a group, and to a household member. The research presented here measures extended financial literacy under these various scaffolds. Financial literacy reflects an individual’s knowledge about financial matters, including the management of risks. The research assesses subjects’ knowledge about interest and inflation, budgeting, and longevity risk. The techniques used to measure literacy reflect state-of-the-art advances in subjective belief elicitation that allow for the recovery of each decisionmaker’s entire underlying subjective distribution. This method generates a rich characterization of subjects’ beliefs and allows the construction of various measures of literacy, welfare, bias, and confidence with respect to a known, true answer. Using controlled laboratory and artefactual field experiments with real rewards and incentivized elicitation of beliefs, we find that these scaffolds reliably enhance literacy. We relate the notion of extended literacy to concepts in economics, cognitive science and philosophy, such as effective literacy, embedded literacy and embodied literacy.

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West, Daune. « Towards a subjective knowledge elicitation methodology for the development of expert systems ». Thesis, University of Portsmouth, 1991. https://researchportal.port.ac.uk/portal/en/theses/towards-a-subjective-knowledge-elicitation-methodology-for-the-development-of-expert-systems(d63c460a-f71c-492d-9150-15c31becdb5b).html.

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Alkhairy, Ibrahim H. « Designing and Encoding Scenario-based Expert Elicitation for Large Conditional Probability Tables ». Thesis, Griffith University, 2020. http://hdl.handle.net/10072/390794.

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This thesis focuses on the general problem of asking experts to assess the likelihood of many scenarios, when there is insufficient time to ask about all possible scenarios. The challenge addressed here is one of experimental design: How to choose which scenarios are assessed; How to use that limited data to extrapolate information about the scenarios that remain unasked? In a mathematical sense, this problem can be constructed as a problem of expert elicitation, where experts are asked to quantify conditional probability tables (CPTs). Experts may be relied on, for example in the situation when empirical data is unavailable or limited. CPTs are used widely in statistical modelling to describe probabilistic relationships between an outcome and several factors. I consider two broad situations where CPTs are important components of quantitative models. Firstly experts are often asked to quantify CPTs that form the building blocks of Bayesian Networks (BNs). In one case study, CPTs describe how habitat suitability of feral pigs is related to various environmental factors, such as water quality and food availability. Secondly CPTs may also support a sensitivity analysis for large computer experiments, by examining how some outcome changes, as various factors are changed. Another case study uses CPTs to examine sensitivity to settings, for algorithms available through virtual laboratories, to map the geographic distribution of species such as the koala. An often-encountered problem is the sheer amount of information asked of the expert: the number of scenarios. Each scenario corresponds to a row of the CPT, and concerns a particular combination of factors, and the likely outcome. Currently most researchers arrange elicitation of CPTs by keeping the number of rows and columns in the CPT to a minimum, so that they need ask experts about no more than twenty or so scenarios. However in some practical problems, CPTs may need to involve more rows and columns, for example involving more than two factors, or factors which can take on more than two or three possible values. Here we propose a new way of choosing scenarios, that underpin the elicitation strategy, by taking advantage of experimental design to: ensure adequate coverage of all scenarios; and to make best use of the scarce resources like the valuable time of the experts. I show that this can be essentially constructed as a problem of how to better design choice of scenarios to elicit from a CPT. The main advantages of these designs is that they explore more of the design space compared to usual design choices like the one-factor-at-a-time (OFAT) design that underpins the popular encoding approach embedded in “CPT Calculator”. In addition this work tailors an under-utilized scenario-based elicitation method to ensure that the expert’s uncertainty was captured, together with their assessments, of the likelihood of each possible outcome. I adopt the more intuitive Outside-In Elicitation method to elicit the expert’s plausible range of assessed values, rather than the more common and reverse-order approach of eliciting their uncertainty around their best guess. Importantly this plausible range of values is more suitable for input into a new approach that was proposed for encoding scenario-based elicitation: Bayesian (rather than a Frequentist) interpretation. Whilst eliciting some scenarios from large CPTs, another challenge arises from the remaining CPT entries that are not elicited. This thesis shows how to adopt a statistical model to interpolate not only the missing CPT entries but also quantify the uncertainty for each scenario, which is new for these two situations: BNs and sensitivity analyses. For this purpose, I introduce the use of Bayesian generalized linear models (GLMs). The Bayesian updating framework also enables us to update the results of elicitation, by incorporating empirical data. The idea is to utilise scenarios elicited from experts to constructan informative Bayesian “prior” model. Then the prior information (e.g. about scenarios) is combined with the empirical data (e.g. from computer model runs), to update the posterior estimates of plausible outcomes (affecting all scenarios). The main findings showed that Bayesian inference suits the small data problem of encoding the expert’s mental model underlying their assessments, allowing uncertainty to vary about each scenario. In addition Bayesian inference provides rich feedback to the modeller and experts on the plausible influence of factors on the response, and whether any information was gained on their interactions. That information could be pivotal to designing the next phase of elicitation about habitat requirements or another phase of computer models. In this way, the Bayesian paradigm naturally supports a sequential approach to gradually accruing information about the issue at hand. As summarised above, the novel statistical methodology presented in this thesis also contributes to computer science. Specifically computation for Bayesian Networks and sensitivity analyses of large computer experiments can be re-designed to be more efficient. Here the expert knowledge is useful to complement the empirical data to inform a more comprehensive analyses.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Info & Comm Tech
Science, Environment, Engineering and Technology
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Akram, Muhammad Farooq. « A methodology for uncertainty quantification in quantitative technology valuation based on expert elicitation ». Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/47717.

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The management of technology portfolios is an important element of aerospace system design. New technologies are often applied to new product designs to ensure their competitiveness at the time they are introduced to market. The future performance of yet-to-be designed components is inherently uncertain, necessitating subject matter expert knowledge, statistical methods and financial forecasting. Estimates of the appropriate parameter settings often come from disciplinary experts, who may disagree with each other because of varying experience and background. Due to inherent uncertain nature of expert elicitation in technology valuation process, appropriate uncertainty quantification and propagation is very critical. The uncertainty in defining the impact of an input on performance parameters of a system, make it difficult to use traditional probability theory. Often the available information is not enough to assign the appropriate probability distributions to uncertain inputs. Another problem faced during technology elicitation pertains to technology interactions in a portfolio. When multiple technologies are applied simultaneously on a system, often their cumulative impact is non-linear. Current methods assume that technologies are either incompatible or linearly independent. It is observed that in case of lack of knowledge about the problem, epistemic uncertainty is most suitable representation of the process. It reduces the number of assumptions during the elicitation process, when experts are forced to assign probability distributions to their opinions without sufficient knowledge. Epistemic uncertainty can be quantified by many techniques. In present research it is proposed that interval analysis and Dempster-Shafer theory of evidence are better suited for quantification of epistemic uncertainty in technology valuation process. Proposed technique seeks to offset some of the problems faced by using deterministic or traditional probabilistic approaches for uncertainty propagation. Non-linear behavior in technology interactions is captured through expert elicitation based technology synergy matrices (TSM). Proposed TSMs increase the fidelity of current technology forecasting methods by including higher order technology interactions. A test case for quantification of epistemic uncertainty on a large scale problem of combined cycle power generation system was selected. A detailed multidisciplinary modeling and simulation environment was adopted for this problem. Results have shown that evidence theory based technique provides more insight on the uncertainties arising from incomplete information or lack of knowledge as compared to deterministic or probability theory methods. Margin analysis was also carried out for both the techniques. A detailed description of TSMs and their usage in conjunction with technology impact matrices and technology compatibility matrices is discussed. Various combination methods are also proposed for higher order interactions, which can be applied according to the expert opinion or historical data. The introduction of technology synergy matrix enabled capturing the higher order technology interactions, and improvement in predicted system performance.

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Iamsumang, Chonlagarn. « A framework for nuclear facility safeguard evaluation using probabilistic methods and expert elicitation ». Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/76528.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 99-100).
With the advancement of the next generation of nuclear fuel cycle facilities, concerns of the effectiveness of nuclear facility safeguards have been increasing due to the inclusion of highly enriched material and reprocessing capability into fuel cycles. Therefore, an extensive and quantitative safeguard evaluation is required in order for the decision makers to have a consistent measure to verify safeguards level of protection, and to effectively improve the current safeguard scheme. The framework presented in this study provides a systematic method for safeguard evaluation of any nuclear facility. Using scenario analysis approach, a diversion scenario consists of target material, target location, diversion technique, set of tactics to help elude the safeguards, and the amount of material diverted per attempt. The success tree methodology and expert elicitation is used to construct logical models and obtain the probabilities of basic events. Then proliferator diversion success probabilities can be derived from the model for all possible scenarios in a given facility. Using Rokkasho reprocessing facility as an example, diversion pathways, uncertainty, sensitivity, and importance measure analyses are shown. Results from the analyses can be used by the safeguarder to gauge the level of protection provided by the current safeguard scheme, and to identify the weak points for improvements. The safeguarder is able to further analyze the effectiveness of the safeguard scheme for different facility designs, and the cost effectiveness analysis will help the safeguarder allocate limited resources for maximum possible protection against a material diversion.
by Chonlagarn Iamsumang.
S.M.

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Okoli, Justin. « Expert knowledge elicitation in the firefighting domain and the implications for training novices ». Thesis, Middlesex University, 2016. http://eprints.mdx.ac.uk/22940/.

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Background/Purpose: Experienced fireground commanders are often required to make important decisions in time-pressured and dynamic environments that are characterized by a wide range of task constraints. The nature of these environments is such that firefighters are sometimes faced with novel situations that seek to challenge their expertise and therefore necessitate making knowledge-based as opposed to rule-based decisions. The purpose of this study is to elicit the tacitly held knowledge which largely underpinned expert competence when managing non-routine fire incidents. Design/Methodology/Approach: The study utilized a formal knowledge elicitation tool known as the critical decision method (CDM). The CDM method was preferred to other cognitive task analysis (CTA) methods as it is specifically designed to probe the cognitive strategies of domain experts with reference to a single incident that was both challenging and memorable. Thirty experienced firefighters and one staff development officer were interviewed in-depth across different fire stations in the UK and Nigeria (UK=15, Nigeria=16). The interview transcripts were analyzed using the emergent themes analysis (ETA) approach. Findings: Findings from the study revealed 42 salient cues that were sought by experts at each decision point. A critical cue inventory (CCI) was developed and cues were categorized into five distinct types based on the type of information each cue generated to an incident commander. The study also developed a decision making model — information filtering and intuitive decision making model (IFID), which describes how the experienced firefighters were able to make difficult fireground decisions amidst multiple informational sources without having to deliberate on their courses of action. The study also compiled and indexed the elicited tacit knowledge into a competence assessment framework (CAF) with which the competence of future incident commanders could potentially be assessed. Practical Implications: Through the knowledge elicitation process, training needs were identified, and the practical implications for transferring the elicited experts’ knowledge to novice firefighters were also discussed. The four component instructional design model aided the conceptualization of the CDM outputs for training purposes. Originality/Value: Although it is widely believed that experts perform exceptionally well in their domains of practice, the difficulty still lies in finding how best to unmask expert (tacit) knowledge, particularly when it is intended for training purposes. Since tacit knowledge operates in the unconscious realm, articulating and describing it has been shown to be challenging even for experts themselves. This study is therefore timely since its outputs can facilitate the development of training curricula for novices, who then will not have to wait for real fires to occur before learning new skills. This statement holds true particularly in this era where the rate of real fires and therefore the opportunity to gain experience has been on a decline. The current study also presents and discusses insights based on the cultural differences that were observed between the UK and the Nigerian fire service.

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Burge, Janet E. « Knowledge Elicitation for Design Task Sequencing Knowledge ». Digital WPI, 1999. https://digitalcommons.wpi.edu/etd-theses/1062.

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"There are many types of knowledge involved in producing a design (the process of specifying a description of an artifact that satisfies a collection of constraints [Brown, 1992]). Of these, one of the most crucial is the design plan: the sequence of steps taken to create the design (or a portion of the design). A number of knowledge elicitation methods can be used to obtain this knowledge from the designer. The success of the elicitation depends on the match between the knowledge elicitation method used and the information being sought. The difficulty with obtaining design plan information is that this information may involve implicit knowledge, i.e. knowledge that can not be expressed explicitly. In this thesis, an approach is used that combines two knowledge elicitation techniques: one direct, to directly request the design steps and their sequence, and one indirect, to refine this knowledge by obtaining steps and sequences that may be implicit. The two techniques used in this thesis were Forward Scenario Simulation (FSS), a technique where the domain expert describes how the procedure followed to solve it, and Card Sort, a technique where the domain expert is asked to sort items (usually entities in the domain) along different attributes. The Design Ordering Elicitation System (DOES) was built to perform the knowledge elicitation. This system is a web-based system designed to support remote knowledge elicitation: KE performed without the presence of the knowledge engineer. This system was used to administer knowledge elicitation sessions to evaluate the effectiveness of these techniques at obtaining design steps and their sequencing. The results indicate that using an indirect technique together with a direct technique obtains more alternative sequences for the design steps than using the direct technique alone."

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Zampa, Nicholas Joseph. « Structured Expert Judgment Elicitation of Use Error Probabilities for Drug Delivery Device Risk Assessment ». Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10841440.

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In the pharmaceutical industry, estimating the probability of occurrence for use errors and use-error-causes (here forth referred to as use error probabilities) when developing drug delivery devices is hindered by a lack of data, ultimately limiting the ability to conduct robust usability risk assessments. A lack of reliable data is the result of small sample sizes and challenges simulating actual use environments in simulated use studies, compromising the applicability of observed use error rates. Further, post-market surveillance databases and internal complaint databases are limited in their ability to provide reliable data for product development. Inadequate usability risk assessment hinders drug delivery device manufacturers' understanding of safety and efficacy risks. The current industry and regulatory paradigm with respect to use error probabilities is to de-emphasize them, focusing instead of assessing the severity of harms. However, de-emphasis of use error probabilities is not rooted in a belief that probability estimates inherently lack value. Rather, the status quo is based on the absence of suitable methodologies for estimating use error probabilities.

In instances in which data is lacking, engineers and scientist may turn to structured expert judgment elicitation methodologies, in which subjective expert opinions are quantified and aggregated in a scientific manner. This research is a case study in adapting and applying one particular structured expert judgment methodology, Cooke’s Classical model, to human factors experts for estimating use error probabilities for a drug delivery device. Results indicate that a performance-weighted linear pooling of expert judgments significantly outperforms any one expert and an equal-weighted linear pooling. Additionally, this research demonstrates that a performance-weighted linear pooling of expert judgments is statistically accurate, robust to the choice of experts, and robust to choice elicitation questions. Lastly, this research validates the good statistical accuracy of a performance-weighted linear pooling of experts on a new set of use error probabilities, indicating that good expert performance translates to use error probabilities estimates for different devices. Through structured expert judgment elicitation according to Cooke’s Classical model, this research demonstrates that it is possible to reinstall use error probability estimates, with quantified uncertainty, into usability risk assessments for drug delivery devices.

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Livres sur le sujet "Elicitation of expert belief"

D, Diaper, dir. Knowledge elicitation : Principles, techniques, and applications. Chichester : E. Horwood, 1989.

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Ayyub, Bilal M. Elicitation of expert opinions for uncertainty and risks. Boca Raton, Fla : CRC Press, 2001.

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Kornfeld, Ari. Belief-network expert systems. Menlo Park, CA : SRI International, 1990.

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Dave, Hellens, dir. Knowledge elicitation : A practical handbook. New York : Prentice Hall, 1991.

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Swackhamer, Deborah Liebl, et James K. Hammit. Review of EPA's Draft expert elicitation task force white paper. Washington, D.C : U.S. Environmental Protection Agency, Office of the Administrator, Science Advisory Board, 2010.

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Peter, Gärdenfors, dir. Belief revision. Cambridge : Cambridge University Press, 1992.

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Grdenfors, Peter. Belief Revision. Cambridge : Cambridge University Press, 1992.

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West, Daune. Towards a subjective knowledge elicitation methodology for the development of expert systems. Portsmouth : Portsmouth Polytechnic, School of Information Science, 1991.

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J, Bonano E., U.S. Nuclear Regulatory Commission. Division of High-Level Waste Management., Sandia National Laboratories et Sandia Corporation, dir. Elicitation and use of expert judgement in performance assessment for high-level radioactive waste repositories. Washington, DC : Division of High-Level Waste Management, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, 1990.

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United States. Congress. Office of Technology Assessment. et Decision Science Consortium Inc, dir. Personalized decision analysis as an expert elicitation tool : An instructive experience in information security policy. [Washington, D.C.?] : The Office, 1985.

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Chapitres de livres sur le sujet "Elicitation of expert belief"

Hoang, Tuan Nha, Tien Tuan Dao et Marie-Christine Ho Ba Tho. « A Method for Uncertainty Elicitation of Experts Using Belief Function ». Dans Modern Approaches for Intelligent Information and Database Systems, 39–49. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76081-0_4.

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Soares, Marta O., et Laura Bojke. « Expert Elicitation to Inform Health Technology Assessment ». Dans Elicitation, 479–94. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_18.

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Bolger, Fergus. « The Selection of Experts for (Probabilistic) Expert Knowledge Elicitation ». Dans Elicitation, 393–443. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_16.

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Gottschalk, Petter, et Lars Gunnesdal. « Expert Elicitation for Estimation ». Dans White-Collar Crime in the Shadow Economy, 37–48. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75292-1_4.

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Merrick, Jason R. W., et Laura A. Albert. « Expert Judgment Based Nuclear Threat Assessment for Vessels Arriving in the US ». Dans Elicitation, 495–509. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_19.

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Werner, Christoph, Anca M. Hanea et Oswaldo Morales-Nápoles. « Eliciting Multivariate Uncertainty from Experts : Considerations and Approaches Along the Expert Judgement Process ». Dans Elicitation, 171–210. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65052-4_8.

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Leplat, Jacques. « The Elicitation of Expert Knowledge ». Dans NATO ASI Series, 107–22. Berlin, Heidelberg : Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-50329-0_7.

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Dean, Geoff. « Research Project : Expert Elicitation Study ». Dans Neurocognitive Risk Assessment for the Early Detection of Violent Extremists, 61–94. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06719-3_4.

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Yoe, Charles. « Characterizing Uncertainty through Expert Elicitation ». Dans Principles of Risk Analysis, 511–38. Second edition. | Boca Raton : Taylor and Francis, CRC Press, 2019. : CRC Press, 2019. http://dx.doi.org/10.1201/9780429021121-14.

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Sagheb-Tehrani, Mehdi. « Knowledge Elicitation : Towards its Transparency ». Dans Database and Expert Systems Applications, 548. Vienna : Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-7557-6_96.

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Actes de conférences sur le sujet "Elicitation of expert belief"

Profir, Bogdan, Murat Hakki Eres, James Scanlan, Michael Moss et Ron Bates. « Uncertainty Quantification via Elicitation of Expert Judgements ». Dans 16th AIAA Aviation Technology, Integration, and Operations Conference. Reston, Virginia : American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-3459.

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« Pragmatic Expert Elicitation for Defence Capability Analysis ». Dans 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.d1.donohoo.

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Ayyub, Bilal M. « Uncertainties in Expert-Opinion Elicitation for Risk Studies ». Dans Ninth United Engineering Foundation Conference on Risk-Based Decisionmaking in Water Resources. Reston, VA : American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40577(306)10.

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Soare, Marta, Muhammad Ammad-Ud-Din et Samuel Kaski. « Regression with n→1 by Expert Knowledge Elicitation ». Dans 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2016. http://dx.doi.org/10.1109/icmla.2016.0131.

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Bauby, C. E., P. Haik, E. Remy, B. Ricard et F. Billy. « Asset Management Evaluation : The Key Role of Expert Elicitation ». Dans ASME 2006 Pressure Vessels and Piping/ICPVT-11 Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/pvp2006-icpvt-11-93237.

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The life management of a nuclear power plant raises several major issues amongst which ranks the aging management of the key components of the plant, both from a technical and an economic point of view. Decision-makers are thus faced with the need to define the best strategy in order to achieve the best possible performance which requires both a very precise modeling of the plant and a detailed analysis of all risks potentially incurred. In this paper, we wish to provide the reader with an overview of how advanced expert elicitation techniques can help identify, structure, quantify and feed sensitive data into a risk-based information system which can then be used for risk-based asset management evaluation. First we focus on the way knowledge management techniques allow EDF to structure and collect life-cycle management data into knowledge-based information systems. The elicitation of component experts is key, particularly in order to get technical information on the future behavior of the component (“anticipation” of whatever events may occur on the plant). We then detail how expert elicitations allow to quantify the probabilities of occurrence of the events: whether there is feedback data, models or not, expert opinion has to be taken into account and mixed, for instance with Bayesian procedures, to this information. Lastly we describe how the information elicited from experts can help top level decision makers get a transverse, long term view on how life management investment strategy translates into plant availability, avoided costs and improved component durability.

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Akram, Farooq, et Dimitri Mavris. « Uncertainty Propagation in Technology Valuation Based on Expert Elicitation ». Dans 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston, Virigina : American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-882.

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Scott, Paul M., Robert Lee Tregoning et Lee Richard Abramson. « Revised LOCA Frequency Estimates From an Expert Elicitation Process ». Dans ASME 2008 Pressure Vessels and Piping Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/pvp2008-61562.

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The double-ended-guillotine break (DEGB) criterion of the largest primary piping system in the plant, which generally provides the limiting condition for the emergency core cooling system requirements, is widely recognized as an extremely unlikely event. As a result, the US Nuclear Regulatory Commission (NRC) is considering a risk-informed revision of the design-basis break size requirements for commercial nuclear power plants. In support of this effort, loss-of-coolant accident (LOCA) frequency estimates were developed using an expert elicitation process by consolidating service history data and insights from probabilistic fracture mechanics (PFM) studies with knowledge of plant design, operation, and material performance. This paper describes, and presents the results for, two of the sensitivity analyses conducted as part of this effort (overconfidence adjustment and aggregation method) to examine the assumptions, structure, and techniques used to process the elicitation responses to develop group estimates of the LOCA frequency estimates.

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Koonchanok, Ratanond, Parul Baser, Abhinav Sikharam, Nirmal Kumar Raveendranath et Khairi Reda. « Data Prophecy : Exploring the Effects of Belief Elicitation in Visual Analytics ». Dans CHI '21 : CHI Conference on Human Factors in Computing Systems. New York, NY, USA : ACM, 2021. http://dx.doi.org/10.1145/3411764.3445798.

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Wang, Shijie, et Marco Valtorta. « A prototype belief network-based expert systems shell ». Dans the third international conference. New York, New York, USA : ACM Press, 1990. http://dx.doi.org/10.1145/98784.98877.

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Singleton, Joseph, et Richard Booth. « Who’s the Expert ? On Multi-source Belief Change ». Dans 19th International Conference on Principles of Knowledge Representation and Reasoning {KR-2022}. California : International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/kr.2022/33.

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Consider the following belief change/merging scenario. A group of information sources give a sequence of reports about the state of the world at various instances (e.g. different points in time). The true states at these instances are unknown to us. The sources have varying levels of expertise, also unknown to us, and may be knowledgeable on some topics but not others. This may cause sources to report false statements in areas they lack expertise. What should we believe on the basis of these reports? We provide a framework in which to explore this problem, based on an extension of propositional logic with expertise formulas. This extended language allows us to express beliefs about the state of the world at each instance, as well as beliefs about the expertise of each source. We propose several postulates, provide a couple of families of concrete operators, and analyse these operators with respect to the postulates.

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Rapports d'organisations sur le sujet "Elicitation of expert belief"

Danz, David, Lise Vesterlund et Alistair Wilson. Belief Elicitation : Limiting Truth Telling with Information on Incentives. Cambridge, MA : National Bureau of Economic Research, juin 2020. http://dx.doi.org/10.3386/w27327.

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Coppersmith, K. J. Unsaturated Zone Flow Model Expert Elicitation Project. Office of Scientific and Technical Information (OSTI), mai 1997. http://dx.doi.org/10.2172/762969.

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Baca, Elena, Ritu Treisa Philip, David Greene et Hoyt Battey. Expert Elicitation for Wave Energy LCOE Futures. Office of Scientific and Technical Information (OSTI), août 2022. http://dx.doi.org/10.2172/1885577.

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Coppersmith, Kevin J., et Roseanne C. Perman. Saturated Zone Flow and Transport Expert Elicitation Project. Office of Scientific and Technical Information (OSTI), janvier 1998. http://dx.doi.org/10.2172/763124.

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Engel, David W., et Angela C. Dalton. CCSI Risk Estimation : An Application of Expert Elicitation. Office of Scientific and Technical Information (OSTI), octobre 2012. http://dx.doi.org/10.2172/1064598.

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Ronald L. Boring, David Gertman, Jeffrey Joe, Julie Marble, William Galyean, Larry Blackwood et Harold Blackman. Simplified Expert Elicitation Procedure for Risk Assessment of Operating Events. Office of Scientific and Technical Information (OSTI), juin 2005. http://dx.doi.org/10.2172/911228.

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Bratzel, D. R. Flammable gas project expert elicitation results for Hanford Site double-shell tanks. Office of Scientific and Technical Information (OSTI), juillet 1998. http://dx.doi.org/10.2172/348862.

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K.J. Coppersmith, R.C. Perman et R.R. Youngs. Lessons Learned- The Use of Formal Expert Elicitation in Probablistic Seismic Hazard. Office of Scientific and Technical Information (OSTI), mai 2006. http://dx.doi.org/10.2172/893709.

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Bratzel, D. R. Flammable gas double shell tank expert elicitation presentations (Part A and Part B). Office of Scientific and Technical Information (OSTI), avril 1998. http://dx.doi.org/10.2172/10148313.

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Farmer, J. C. ,LLNL. Waste package degradation expert elicitation panel : input on corrosion of CRM alloy C-22. Office of Scientific and Technical Information (OSTI), mars 1998. http://dx.doi.org/10.2172/289846.

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