Relevant bibliographies by topics / Model credibility assessment

Academic literature on the topic 'Model credibility assessment'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Model credibility assessment"

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Pryor, S. C., and J. T. Schoof. "Differential Credibility Assessment for Statistical Downscaling." Journal of Applied Meteorology and Climatology 59, no. 8 (August 1, 2020): 1333–49. http://dx.doi.org/10.1175/jamc-d-19-0296.1.

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AbstractClimate science is increasingly using (i) ensembles of climate projections from multiple models derived using different assumptions and/or scenarios and (ii) process-oriented diagnostics of model fidelity. Efforts to assign differential credibility to projections and/or models are also rapidly advancing. A framework to quantify and depict the credibility of statistically downscaled model output is presented and demonstrated. The approach employs transfer functions in the form of robust and resilient generalized linear models applied to downscale daily minimum and maximum temperature anomalies at 10 locations using predictors drawn from ERA-Interim reanalysis and two global climate models (GCM; GFDL-ESM2M and MPI-ESM-LR). The downscaled time series are used to derive several impact-relevant Climate Extreme (CLIMDEX) temperature indices that are assigned credibility based on 1) the reproduction of relevant large-scale predictors by the GCMs (i.e., fraction of regression beta weights derived from predictors that are well reproduced) and 2) the degree of variance in the observations reproduced in the downscaled series following application of a new variance inflation technique. Credibility of the downscaled predictands varies across locations and between the two GCM and is generally higher for minimum temperature than for maximum temperature. The differential credibility assessment framework demonstrated here is easy to use and flexible. It can be applied as is to inform decision-makers about projection confidence and/or can be extended to include other components of the transfer functions, and/or used to weight members of a statistically downscaled ensemble.
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Wauchope, R. Don. "Environmental Risk Assessment of Pesticides: Improving Simulation Model Credibility." Weed Technology 6, no. 3 (September 1992): 753–59. http://dx.doi.org/10.1017/s0890037x00036162.

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Registrant use of computer simulation modeling is generally accepted by regulators in lieu of some experimental data for risk assessment, provided worst-case assumptions and extremely conservative criteria for negligible risk are used. These requirements taken together mean that only extreme cases escape the requirement for actual environmental data. This conservatism reflects the uncertainty in both exposure estimates by the models and in the hazard estimates from toxicologists. Until the credibility of estimated environmental concentrations given by models is improved by more experimental data and experience on the part of both registrants and regulators, the models will continue to be considered not-validated by many. There are four current developments that provide a compromise between the two impossible extremes of total model validation and total field measurement: (1) as models develop more process detail the parameters become more fundamental in nature and these are generally more amenable to independent estimation or measurement; (2) the reporting of probabilistic analyses and probable errors of results by modelers will enhance credibility; (3) the development of data sets for specific crop/site/pesticide/weather scenarios will allow users to modify those parts of the input they are concerned with while retaining confidence that parameters with which they are unfamiliar will have reasonable values; and (4) meso-scale and micro-scale physical simulation experiments can fill the gap between laboratory and field results. The most important need for enhancing model credibility is full access by the pesticide science community to all the information available, so that we may increase our understanding. Legal mechanisms should be considered for longer ownership of exclusive marketing rights of active ingredients, in exchange for complete public disclosure of the environmental fate and toxicology data submitted to regulatory agencies.
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Zhu, Mingxun, Xiaohong Chen, Xinxing Luo, and Fujun Liu. "Software credibility assessment model based on back propagation network." International Journal of Computational Systems Engineering 2, no. 2 (2015): 66. http://dx.doi.org/10.1504/ijcsyse.2015.077069.

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Susanti, Dwi, and Sokono Sukono. "Calculating Premium Credibility Using the Buhlmann-Straub Modelwith Nonparametric Assessment." International Journal of Global Operations Research 1, no. 1 (February 4, 2020): 20–32. http://dx.doi.org/10.47194/ijgor.v1i1.15.

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When an insurance company calculates the premium it will divides the policy holders into groups. The division is considered based on risk level in each group. The problem is then to devise a way of combining the experience risk of the group with the experience of the individual risk to calculate the premium, so then Credibility Theory provides a solution to this problem.This script discuss about calculation of credibility premium use Buhlmann-Straub Model with nonparametric estimation to the aggregate claim amount data set within few years observation in some group of policy holders in general insurance. By using credibility theory we can calculate the value of credibility factor and credibility premium or future premium. The value of premium credibility is calculated from only one group of policyholders from the previous year's data. For better value of premium credibility, data with more experience years and the policyholder group better reflect the total loss value during the observation year.The result of this calculation are credibility factor per group, average credibility premium per members in group and credibility premium total for the last year for each group. We can obtain total losses and total premium which surprisingly equal.
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Yao, Jinglong, Ling Xing, and Honghai Wu. "A Microblog Content Credibility Evaluation Model Based on the Influence of Sentiment Polarity." Mobile Information Systems 2022 (May 31, 2022): 1–11. http://dx.doi.org/10.1155/2022/8983534.

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False content in microblogs affects users’ judgment of facts. An evaluation of microblog content credibility can find false information as soon as possible, which ensures that social networks maintain a positive environment. The influence of sentiment polarity can be used to analyze the correlation between sentiment polarity in comments and Weibo content through semantic features and sentiment features in comments, to improve the effect of content credibility assessment. This paper proposes a Weibo content credibility evaluation model, CEISP (Credibility Evaluation based on the Influence of Sentiment Polarity). The semantic features of microblog content are extracted by a bidirectional-local information processing network. Bidirectional long short-term memory (BiLSTM) is used to mine the sentiment features of comments. The attention mechanism is used to capture the impact of different sentiment polarities in comments on microblog content, and the influence of sentiment polarities is obtained for the credibility assessment of microblog content. The experimental results on real datasets show that the evaluation performance of the CEISP model is improved compared with the comparison model. Compared with the existing Att-BiLSTM model, the evaluation accuracy of the CEISP model is improved by 0.0167.
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Shafqat, Wafa, Yung-Cheol Byun, and Namje Park. "Effectiveness of Machine Learning Approaches Towards Credibility Assessment of Crowdfunding Projects for Reliable Recommendations." Applied Sciences 10, no. 24 (December 18, 2020): 9062. http://dx.doi.org/10.3390/app10249062.

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Recommendation systems aim to decipher user interests, preferences, and behavioral patterns automatically. However, it becomes trickier to make the most trustworthy and reliable recommendation to users, especially when their hardest earned money is at risk. The credibility of the recommendation is of magnificent importance in crowdfunding project recommendations. This research work devises a hybrid machine learning-based approach for credible crowdfunding projects’ recommendations by wisely incorporating backers’ sentiments and other influential features. The proposed model has four modules: a feature extraction module, a hybrid LDA-LSTM (latent Dirichlet allocation and long short-term memory) based latent topics evaluation module, credibility formulation, and recommendation module. The credibility analysis proffers a process of correlating project creator’s proficiency, reviewers’ sentiments, and their influence to estimate a project’s authenticity level that makes our model robust to unauthentic and untrustworthy projects and profiles. The recommendation module selects projects based on the user’s interests with the highest credible scores and recommends them. The proposed recommendation method harnesses numeric data and sentiment expressions linked with comments, backers’ preferences, profile data, and the creator’s credibility for quantitative examination of several alternative projects. The proposed model’s evaluation depicts that credibility assessment based on the hybrid machine learning approach contributes efficient results (with 98% accuracy) than existing recommendation models. We have also evaluated our credibility assessment technique on different categories of the projects, i.e., suspended, canceled, delivered, and never delivered projects, and achieved satisfactory outcomes, i.e., 93%, 84%, 58%, and 93%, projects respectively accurately classify into our desired range of credibility.
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Feng, Yanling, Jixiong Hu, Rui Duan, and Zhuming Chen. "Credibility Assessment Method of Sensor Data Based on Multi-Source Heterogeneous Information Fusion." Sensors 21, no. 7 (April 5, 2021): 2542. http://dx.doi.org/10.3390/s21072542.

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The credibility of sensor data is essential for security monitoring. High-credibility data are the precondition for utilizing data and data analysis, but the existing data credibility evaluation methods rarely consider the spatio-temporal relationship between data sources, which usually leads to low accuracy and low flexibility. In order to solve this problem, a new credibility evaluation method is proposed in this article, which includes two factors: the spatio-temporal relationship between data sources and the temporal correlation between time series data. First, the spatio-temporal relationship was used to obtain the credibility of data sources. Then, the combined credibility of data was calculated based on the autoregressive integrated moving average (ARIMA) model and back propagation (BP) neural network. Finally, the comprehensive data reliability for evaluating data quality can be acquired based on the credibility of data sources and combined data credibility. The experimental results show the effectiveness of the proposed method.
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Wang, Bowen, Haitao Xiong, and Chengrui Jiang. "A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/347619.

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As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.
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Zhong, Yin Zhen, Min Xia Liu, and Wei Chun Gao. "An Improved Education Evaluation Model Based on SEEQ." Advanced Materials Research 926-930 (May 2014): 4457–60. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.4457.

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In order to improve the credibility of vocational teaching evaluation, the paper summarizes the traditional SEEQ evaluation model, and analyzes some existing deficiencies. Combined with the demand of current teaching evaluation, a kind of improved teaching evaluation model-VSEEQ is proposed. The model increases two new evaluation dimensions. Through the research sampling, the data is conducted the KMO and Bartlett analysis. The experiment can show that VSEEQ evaluation result can accurately reflect the practical issue existed in the teaching, thus greatly improving the credibility of teaching assessment.
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Tashtoush, Yahya M., Aisha Zaidan, and Izzat M. Alsmadi. "Implications for Website Trust and Credibility Assessment." International Journal of E-Entrepreneurship and Innovation 3, no. 4 (October 2012): 17–33. http://dx.doi.org/10.4018/jeei.2012100102.

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With the expansion of the Internet services provided to users to cover almost all areas that were dominated by traditional face-to-face and location based businesses, one of the major challenges for such expansion is security and its related concerns. Customers or users need to trust the websites they visit in terms of the information or content. This research proposes a new formula for evaluating the credibility (called XD TRank) metric of websites. A case study of 40 selected websites in Jordan is used to assess the proposed credibibility metric. The metrics required to assess Websites and pages credibility are collected and evaluated based on 25 existing metrics and built a model using SPSS by applying stepwise linear regression analysis to predict the XD TRank. Results showed that there is a broad range of metrics that affect the credibility of a website or a webpage and their impact on credibility may vary on their significancy or impact on the trust rank metric. For e-business in particular, trust rank metrics can be used part of quality assurance and auditing processes. Those can be important assets for users to be able to distinguish known, popular and reliable e-commerce websites from spammers or websites which try to trick novice users. Trust rank can be also used like a logo in all Website pages to alert users if they were redirected to phishing pages.
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Dissertations / Theses on the topic "Model credibility assessment"

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Moffitt, Kevin Christopher. "Toward Enhancing Automated Credibility Assessment: A Model for Question Type Classification and Tools for Linguistic Analysis." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145456.

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The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt Question Type Model (MQTM) was developed to aid in predicting linguistic features of responses to questions. It focuses on three context independent features of questions: tense (past vs. present vs. future), perspective (introspective vs. extrospective), and abstractness (concrete vs. conjectural). The MQTM was tested on responses to real-world pre-polygraph examination questions in which guilty (n = 27) and innocent (n = 20) interviewees were interviewed. The responses were grouped according to question type and the linguistic cues from each groups' transcripts were compared using independent samples t-tests with the following results: future tense questions elicited more future tense words than either past or present tense questions and present tense questions elicited more present tense words than past tense questions; introspective questions elicited more cognitive process words and affective words than extrospective questions; and conjectural questions elicited more auxiliary verbs, tentativeness words, and cognitive process words than concrete questions. Second, a tool for linguistic analysis of text documents, Structured Programming for Linguistic Cue Extraction (SPLICE), was developed to help researchers and software developers compute linguistic values for dictionary-based cues and cues that require natural language processing techniques. SPLICE implements a GUI interface for researchers and an API for developers. Finally, an analysis of 560 lexical bundles detected linguistic differences between 101 fraudulent and 101 non-fraudulent 10-K filings. Phrases such as "the fair value of," and "goodwill and other intangible assets" were used at a much higher rate in fraudulent 10-Ks. A principal component analysis reduced the number of variables to 88 orthogonal components which were used in a discriminant analysis that classified the documents with 71% accuracy. Findings in this dissertation suggest the MQTM could be used to predict features of interviewee responses in most contexts and that lexical bundle analysis is a viable tool for discriminating between fraudulent and non-fraudulent text.
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Yeo, Keng Leong Actuarial Studies Australian School of Business UNSW. "Claim dependence in credibility models." Awarded by:University of New South Wales. School of Actuarial Studies, 2006. http://handle.unsw.edu.au/1959.4/25971.

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Existing credibility models have mostly allowed for one source of claim dependence only, that across time for an individual insured risk or a group of homogeneous insured risks. Numerous circumstances demonstrate that this may be inadequate and insufficient. In this dissertation, we developed a two-level common effects model, based loosely on the Bayesian model, which allows for two possible sources of dependence, that across time for the same individual risk and that between risks. For the case of Normal common effects, we are able to derive explicit formulas for the credibility premium. This takes the intuitive form of a weighted average between the individual risk's claims experience, the group's claims experience and the prior mean. We also consider the use of copulas, a tool widely used in other areas of work involving dependence, in constructing credibility premiums. Specifically, we utilise copulas to model the dependence across time for an individual risk or group of homogeneous risks. We develop the construction with several well-known families of copulas and are able to derive explicit formulas for their respective conditional expectations. Whilst some recent work has been done on constructing credibility models with copulas, explicit formulas for the conditional expectations have rarely been made available. Finally, we calibrate these copula credibility models using a real data set. This data set relates to the claims experience of workers' compensation insurance by occupation over a 7-year period for a particular state in the United States. Our results show that for each occupation, claims dependence across time is indeed present. Amongst the copulas considered in our empirical analysis, the Cook-Johnson copula model is found to be the best fit for the data set used. The calibrated copula models are then used for prediction of the next period's claims. We found that the Cook-Johnson copula model gives superior predictions. Furthermore, this calibration exercise allowed us to uncover the importance of examining the nature of the data and comparing it with the characteristics of the copulas we are calibrating to.
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Rondzíková, Martina. "Hodnocení finančního zdraví podniku XY/ Assessment of financial health of enterprise XY." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-124938.

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This thesis deals with the evaluation of the financial health of the company from 2006 to 2010. The reference is now a limited liability company in the Pardubice region. Result of this work is to implement an external financial analysis of the selected company and application credibility and bankruptcy models. The theoretical part is focused on general characteristics of financial health, financial analysis and credibility and bankruptcy models. The practical part deals with analysis of the company. This analysis focuses on the analysis of financial statements, ratios, and finally the application of credibility and bankruptcy models.
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Books on the topic "Model credibility assessment"

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Nash, Franklin R. Estimating device reliability: Assessment of credibility. Boston: Kluwer Academic Publishers, 1993.

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Sheppard, Marsha I. Methodology for evaluating the credibility and reliability of models for environmental impact assessment. Pinawa, Man: AECL, Whiteshell Laboratories, 1996.

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Nash, Franklin R. Estimating Device Reliability:: Assessment of Credibility (The Springer International Series in Engineering and Computer Science). Springer, 1992.

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Burris, Scott, Micah L. Berman, Matthew Penn, and, and Tara Ramanathan Holiday. Using Evidence and Knowledge Critically in Policy Development. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190681050.003.0007.

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This chapter starts with the recognition that policymaking usually precedes evidence of what laws are effective in solving the problem at hand. That does not mean that policymaking cannot be guided by evidence. Policymakers can usually draw on extensive evidence defining the problem and evidence of analogous policy cases. This chapter identifies sources of policy recommendations and direct evidence of policy impact, including systematic reviews, narrative reviews, models, cost-benefit analysis, and individual studies. It reviews strategies for identifying bias and source credibility and tools for “educated guessing” about policy options in matters where evidence is scarce or incomplete, including causal mapping and the Haddon matrix. Finally, it introduces the Health in All Policies approach and the use of health impact assessments as tools to consider broader impact and cross-sectoral cooperation.
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Kwame Harrison, Anthony. Discussion and Evaluation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199371785.003.0005.

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Chapter 5 begins with a general discussion of the central research paradigms that ethnographers claim and/or move between. The remainder of the chapter is organized according to the evaluative standards used by the various stakeholders who surround the ethnographic enterprise—namely, researchers, members of researched communities, and readers. The section on researchers is centered on their aspirations to do “good work,” which the author proposes involves reflexivity, transparency, and sincerity. It also elaborates on the moral principles and ethical regulations that ethnographic researchers observe. In discussing members of researched communities, the author highlights their recent ability to speak back against the research, explaining how it has fostered more accountable and collaborative modes of ethnography. Finally, in discussing readers of ethnography, the author makes a distinction between “everyday” and “professional” readers, proposing a handful of criteria—credibility, coherence, impact, and worthiness—used by the latter in making their professional assessments.
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Book chapters on the topic "Model credibility assessment"

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Alrubaian, Majed, Muhammad Al-Qurishi, Mabrook Al-Rakhami, and Atif Alamri. "A Credibility Assessment Model for Online Social Network Content." In Lecture Notes in Social Networks, 61–77. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51367-6_3.

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Tan, Wee-Kheng, and Yu-Chung Chang. "Credibility Assessment Model of Travel Information Sources: An Exploratory Study on Travel Blogs." In Information and Communication Technologies in Tourism 2011, 457–69. Vienna: Springer Vienna, 2011. http://dx.doi.org/10.1007/978-3-7091-0503-0_37.

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Rider, W. J., W. R. Witkowski, and Vincent A. Mousseau. "Uncertainty Quantification’s Role in Modeling and Simulation Planning, and Credibility Assessment Through the Predictive Capability Maturity Model." In Handbook of Uncertainty Quantification, 1589–612. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-12385-1_51.

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Rider, W. J., W. R. Witkowski, and Vince Mousseau. "Uncertainty Quantification’s Role in Modeling and Simulation Planning, and Credibility Assessment Through the Predictive Capability Maturity Model." In Handbook of Uncertainty Quantification, 1–23. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11259-6_51-1.

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Carter, Timothy R., and Stefan Fronzek. "A Model-Based Response Surface Approach for Evaluating Climate Change Risks and Adaptation Urgency." In Springer Climate, 67–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86211-4_9.

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AbstractWe present a new approach to advance methods of climate change impact and adaptation assessment within a risk framework. Specifically, our research seeks to test the feasibility of applying impact models across sectors within a standard analytical framework for representing three aspects of potential relevance for policy: (i) sensitivity—examining the sensitivity of the sectors to changing climate for readily observable indicators; (ii) urgency—estimating risks of approaching or exceeding critical thresholds of impact under alternative scenarios as a basis for determining urgency of response; and (iii) response—determining the effectiveness of potential adaptation and mitigation responses. By working with observable indicators, the approach is also amenable to long-term monitoring as well as evaluation of the success of adaptation, where this too can be simulated. The approach focuses on impacts in climate-sensitive sectors, such as water resources, forestry, agriculture or human health. It involves the construction of impact response surfaces (IRSs) based on impact model simulations, using sectoral impact models that are also capable of simulating some adaptation measures. We illustrate the types of analyses to be undertaken and their potential outputs using two examples: risks of crop yield shortfall in Finland and impact risks for water management in the Vale do Gaio reservoir, Portugal. Based on previous analyses such as these, we have identified three challenges requiring special attention in this new modelling exercise: (a) ensuring the salience and credibility of the impact modelling conducted and outputs obtained, through engagement with relevant stakeholders, (b) co-exploration of the capabilities of current impact models and the need for improved representation of adaptation and (c) co-identification of critical thresholds for key impact indicators and effective representation of uncertainties. The approach is currently being tested for five sectors in Finland.
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Rubin, Victoria L. "Credibility Assessment Models and Trust Indicators in Social Sciences." In Misinformation and Disinformation, 61–94. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95656-1_3.

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Chihfeng, Kuan, Keith W. Bedford, and David J. Schwab. "A preliminary credibility analysis of the Lake Erie portion of the Great Lakes Forecasting System for springtime heating conditions." In Quantitative Skill Assessment for Coastal Ocean Models, 397–423. Washington, D. C.: American Geophysical Union, 1995. http://dx.doi.org/10.1029/ce047p0397.

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Yang, Xiaojun, Zhongfu Xu, Chuan Shi, Hao Lei, and Changwei Yan. "Credibility Assessment of Simulation Models Using Hesitant Cloud Linguistic Term Sets." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 856–63. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32456-8_92.

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Yang, Xiaojun, Zhongfu Xu, Rongmao He, and Fangxia Xue. "Credibility Assessment of Complex Simulation Models Using Cloud Models to Represent and Aggregate Diverse Evaluation Results." In Intelligent Computing Methodologies, 306–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26766-7_28.

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Kaufhold, Marc-André, Markus Bayer, Daniel Hartung, and Christian Reuter. "Design and Evaluation of Deep Learning Models for Real-Time Credibility Assessment in Twitter." In Lecture Notes in Computer Science, 396–408. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86383-8_32.

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Conference papers on the topic "Model credibility assessment"

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Madry, John G., James N. Elele, David H. Hall, and David J. Turner. "Risk Assessment for Model and Simulation Credibility Characteristics." In ASME 2019 Verification and Validation Symposium. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/vvs2019-5152.

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Abstract The Department of Defense (DoD) uses the principles of risk assessment extensively throughout the acquisition process to identify, manage, and mitigate risk in many areas including software (both simulation software and software embedded in materiel systems). The approach to assessing the risks associated with using results from Models and Simulations (M&S) to influence decision-making that is described here is used by the Naval Air Systems Command (NAVAIR) 5.4H Verification, Validation, and Accreditation office. The focus of the risk assessment is on ten specific characteristics of M&S Capability, Accuracy, and Usability that have the most potential impact on the intended uses. In this method, the characteristics of the M&S are evaluated against standard criteria, and then assigned a color-rating of Green, Yellow, or Red based on the actual data obtained from the M&S itself. A simple computation is then used to weigh the ratings of the characteristics into the likelihood of error aspect of the risk of using the M&S. A thorough understanding of the M&S and its application is a prerequisite to using this approach since the analyst is required to provide a technical justification for the rating assigned to a characteristic. Should the assigned rating for a characteristic of the M&S not be green, the analyst is required to recommend actions and/or mitigations for the M&S developer to take that would improve the rating to green.
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Zan, Songting, and Xu Zhang. "Medical Data Quality Assessment Model Based on Credibility Analysis." In 2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC). IEEE, 2018. http://dx.doi.org/10.1109/itoec.2018.8740576.

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Wang, Haoliang, Qingdong Li, and Zhang Ren. "Control-oriented credibility assessment of air-breathing hypersonic vehicle model." In 2017 29th Chinese Control And Decision Conference (CCDC). IEEE, 2017. http://dx.doi.org/10.1109/ccdc.2017.7979050.

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Saoud, Zohra, Noura Faci, Zakaria Maamar, and Djamal Benslimane. "A Fuzzy Clustering-Based Credibility Model for Trust Assessment in a Service-Oriented Architecture." In 2014 IEEE 23rd International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprise (WETICE). IEEE, 2014. http://dx.doi.org/10.1109/wetice.2014.35.

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Mitchell, Kenneth N., and Sankaran Mahadevan. "Model Uncertainty in Fluid-Structure Impact Risk Analysis." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-16189.

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This paper investigates the issue of model uncertainty in risk assessments of fluid-structure impact problems. Model-based risk assessments of complex phenomena such as the space shuttle solid rocket booster (SRB) splashdown event is affected by significant model uncertainty and approximations in finite element discretization, damage modeling, and the probabilistic analysis. Model verification and validation (V&V) helps in systematic assessment of modeling error, and suitable V&V techniques are explored in this paper. Since experimental testing of the SRB is infeasible, a simplified experimental framework is devised using an aluminum cylinder hinged at one end, with the objective of providing insights into the required model form (validation) as well as the required model resolution (verification). Preliminary results from error quantification as well as experimental validation are presented and discussed. Such information could be used to develop confidence and credibility in real-world reliability predictions of fluid-structure impact problems such as SRB splashdown.
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Pai, Shantaram S., and David S. Riha. "Model Verification and Validation Concepts for a Probabilistic Fracture Assessment Model to Predict Cracking of Knife Edge Seals in the Space Shuttle Main Engine High Pressure Oxidizer." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-70132.

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Physics-based models are routinely used to predict the performance of engineered systems to make decisions such as when to retire system components, how to extend the life of an aging system, or if a new design will be safe or available. Model verification and validation (V&V) is a process to establish credibility in model predictions. Ideally, carefully controlled validation experiments will be designed and performed to validate models or submodels. In reality, time and cost constraints limit experiments and even model development. This paper describes elements of model V&V during the development and application of a probabilistic fracture assessment model to predict cracking in space shuttle main engine high-pressure oxidizer turbopump knife-edge seals. The objective of this effort was to assess the probability of initiating and growing a crack to a specified failure length in specific flight units for different usage and inspection scenarios. The probabilistic fracture assessment model developed in this investigation combined a series of submodels describing the usage, temperature history, flutter tendencies, tooth stresses and numbers of cycles, fatigue cracking, nondestructive inspection, and finally the probability of failure. The analysis accounted for unit-to-unit variations in temperature, flutter limit state, flutter stress magnitude, and fatigue life properties. The investigation focused on the calculation of relative risk rather than absolute risk between the usage scenarios. Verification predictions were first performed for three units with known usage and cracking histories to establish credibility in the model predictions. Then, numerous predictions were performed for an assortment of operating units that had flown recently or that were projected for future flights. Calculations were performed using two NASA-developed software tools: NESSUS® for the probabilistic analysis, and NASGRO® for the fracture mechanics analysis. The goal of these predictions was to provide additional information to guide decisions on the potential of reusing existing and installed units prior to the new design certification.
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Buzzetto-More, Nicole, and Ayodele Alade. "The Pentagonal E-Portfolio Model for Selecting Adopting Building and Implementing an E-Portfolio." In InSITE 2008: Informing Science + IT Education Conference. Informing Science Institute, 2008. http://dx.doi.org/10.28945/3240.

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Electronic portfolios are a student-centered outcomes-based assessment regime involving learners in the gathering, selection, and organization of artifacts synthesized into a compilation purposed to demonstrate knowledge, skills, and/or achievements supported by reflections that articulate the relevance, credibility, and meaning of the artifacts being presented. Electronic portfolios have been found to be a valid way to document student progress, encourage student involvement in assessment, showcase student work samples, promote students professionally, and provide a method of student learning outcomes and curriculum evaluation. However, electronic portfolio adoption represents a sizable commitment that is influenced by a number of variables and that requires foresight as well as a thoughtful strategy. This paper presents a model for selecting, designing, and implementing an electronic portfolio project and illustrates its application through the presentation of a detailed case study of a successfully implemented and ongoing electronic portfolio project used as a comprehensive assessment measure to determine degree mastery in the Department of Business, Management, and Accounting at the University of Maryland Eastern Shore. The model introduced in this paper is known as the Pentagonal E-Portfolio Model, named such for its five levels: 1) Level 1 - Identification of Needs; 2) Level 2 - Determination, Assessment, & Budgeting; 3) Level 3 - System Selection and Strategic Planning; 4) Level 4 - Development; and 5) Level 5 - Implementation and Continuation.
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Oberst, Ala, and Maria Gheorghita. "Consolidate the reputation and increase the credibility of the company through the implementation of the social audit." In 4th Economic International Conference "Competitiveness and Sustainable Development". Technical University of Moldova, 2022. http://dx.doi.org/10.52326/csd2022.18.

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An organization’s commitment to the welfare of society has become a central criterion in measuring its overall performance and its ability to continue to operate effectively. The role of the social audit is an essential one in the process of qualitative assessment of the organizational capacity to manage human resources in order to determine the social impact. The main objective established in carrying out this research consists in highlighting the most widely spread international models for social audit that can be applied as a reference by companies from the Republic of Moldova. The selection and application of the most appropriate social audit model will allow enterprises to carry out self-assessment and identify directions for increasing social responsibility to protect and increase reputation, to improve the image and strengthen the organizational culture, to increase the trust of customers and business partners.
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Ben-Haim, Yakov, and Franc¸ois M. Hemez. "Robustness, Fidelity and Prediction-Looseness of Models." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58008.

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Assessment of the credibility of a mathematical or numerical model of an engineering system must combine three components: (1) The fidelity of the model to test data. (2) The robustness, of model fidelity, to lack of understanding of the underlying processes. (3) The prediction looseness of the model. ‘Prediction looseness’ is the range of predictions of models which are equivalent in terms of fidelity. The main result of this paper is that high fidelity, high robustness, and small prediction looseness are mutually incompatible. A model with high fidelity to data and high robustness to imperfect understanding of the process, will have low predictive focus. Our analysis is based on info-gap models of uncertainty.
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Tan, Jingye, Kathryn Maupin, Shuai Shao, and Danial Faghihi. "A Bayesian Machine Learning Framework for Selection of the Strain Gradient Plasticity Multiscale Model." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-69693.

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Abstract A class of sequential multiscale models investigated in this study consists of discrete dislocation dynamics (DDD) simulations and continuum strain gradient plasticity (SGP) models to simulate the size effect in plastic deformation of metallic micropillars. The high-fidelity DDD explicitly simulates the microstructural (dislocation) interactions. These simulations account for the effect of dislocation densities and their spatial distributions on plastic deformation. The continuum SGP captures the size-dependent plasticity in micropillars using two length parameters. The main challenge in predictive DDD-SGP multi-scale modeling is selecting the proper constitutive relations for the SGP model, which is necessitated by the uncertainty in computational prediction due to DDD’s microstructural randomness. This contribution addresses these challenges using a Bayesian learning and model selection framework. A family of SGP models with different fidelities and complexities is constructed using various constitutive relation assumptions. The parameters of the SGP models are then learned from a set of training data furnished by the DDD simulations of micropillars. Bayesian learning allows the assessment of the credibility of plastic deformation prediction by characterizing the microstructural variability and the uncertainty in training data. Additionally, the family of the possible SGP models is subjected to a Bayesian model selection to pick the model that adequately explains the DDD training data. The framework proposed in this study enables learning the physics-based multiscale model from uncertain observational data and determining the optimal computational model for predicting complex physical phenomena, i.e., size effect in plastic deformation of micropillars.
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Reports on the topic "Model credibility assessment"

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Савченко, Лариса Олексіївна. Characteristic of the future specialists professional preparation to the quality educational assessment. Педагогічна думка, 2015. http://dx.doi.org/10.31812/0564/365.

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To consider the characteristics of the levels of formation of professional readiness of future specialists to pedagogical diagnostics of quality of education. Diagnostics of levels of formation of professional training of future teachers is realized through a number of research methods: observation, testing, interview, analysis of the results. The basis of the diagnostic systems research on three-level assessment scale, supplemented by «high level», which allows to adapt to local conditions and to enrich the features of a particular region. Analysis of modern works on the organization of control of educational achievements of students; the log books of progress and attendance of students in classes, conversations with teachers and our own observations have proved that in educational practice there are different models of the organization of control of educational achievements of students in pedagogical disciplines and professional subject training, validation should be carried out using various schemes and scales of evaluation present different approaches to the calculation of rating of students (in some cases even within the same University) and others. The analysis proved that the existing complex control tasks and tasks for independent work is only seventy percent of jobs differentiated by professional orientation, the rest of the job for the overall development of pedagogical competence of students. In our opinion, well developed task, that is, those that consist mainly of problems of professional and pedagogical orientation that enhance future teachers ‘ motivation to learn pedagogical disciplines. The quality of education becomes the main reference point that determines the credibility and competitiveness of educational institutions on regional, national level and international arena.
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