Academic literature on the topic 'Mixed meta-model'
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Journal articles on the topic "Mixed meta-model"
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Kalaian, Hripsime A., and Stephen W. Raudenbush. "A multivariate mixed linear model for meta-analysis." Psychological Methods 1, no. 3 (1996): 227–35. http://dx.doi.org/10.1037/1082-989x.1.3.227.
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LeBeau, Brandon, Yoon Ah Song, and Wei Cheng Liu. "Model Misspecification and Assumption Violations With the Linear Mixed Model: A Meta-Analysis." SAGE Open 8, no. 4 (October 2018): 215824401882038. http://dx.doi.org/10.1177/2158244018820380.
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This meta-analysis attempts to synthesize the Monte Carlo (MC) literature for the linear mixed model under a longitudinal framework. The meta-analysis aims to inform researchers about conditions that are important to consider when evaluating model assumptions and adequacy. In addition, the meta-analysis may be helpful to those wishing to design future MC simulations in identifying simulation conditions. The current meta-analysis will use the empirical type I error rate as the effect size and MC simulation conditions will be coded to serve as moderator variables. The type I error rate for the fixed and random effects will be explored as the primary dependent variable. Effect sizes were coded from 13 studies, resulting in a total of 4,002 and 621 effect sizes for fixed and random effects respectively. Meta-regression and proportional odds models were used to explore variation in the empirical type I error rate effect sizes. Implications for applied researchers and researchers planning new MC studies will be explored.
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Stram, Daniel O. "Meta-Analysis of Published Data Using a Linear Mixed-Effects Model." Biometrics 52, no. 2 (June 1996): 536. http://dx.doi.org/10.2307/2532893.
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Barbillon, Pierre, Célia Barthélémy, and Adeline Samson. "Parameter estimation of complex mixed models based on meta-model approach." Statistics and Computing 27, no. 4 (June 22, 2016): 1111–28. http://dx.doi.org/10.1007/s11222-016-9674-x.
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Shim, Minjung, Burke Johnson, Joke Bradt, and Susan Gasson. "A Mixed Methods–Grounded Theory Design for Producing More Refined Theoretical Models." Journal of Mixed Methods Research 15, no. 1 (June 8, 2020): 61–86. http://dx.doi.org/10.1177/1558689820932311.
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Current literature lacks explication of how traditional grounded theory and mixed methods–grounded theory (MM-GT) are similar/different and specific explication of how to construct MM-GT designs—our purpose is to do this. We illustrate the design process using a published study. Exploratory Phase 1 involves creation of a formative–theoretical model based on multiple implicit or explicit models identified in the literature, which are then combined into a single model using meta-modeling integration. Also, in Phase 1, a traditional grounded theory is developed “independently” using interview data. These two models are integrated into a combined/meta-model at the end of Phase 1. Confirmatory Phase 2 involves testing of the final Phase 1 meta-model using a mixed methods experiment. In Phase 3, the Phase 1 and Phase 2 results are integrated, producing the “final” meta-model. This article contributes to the field of mixed methods research by showing how to design an MM-GT study that is focused on theory development and testing.
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Nikoloulopoulos, Aristidis K. "Hybrid copula mixed models for combining case-control and cohort studies in meta-analysis of diagnostic tests." Statistical Methods in Medical Research 27, no. 8 (December 21, 2016): 2540–53. http://dx.doi.org/10.1177/0962280216682376.
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Copula mixed models for trivariate (or bivariate) meta-analysis of diagnostic test accuracy studies accounting (or not) for disease prevalence have been proposed in the biostatistics literature to synthesize information. However, many systematic reviews often include case-control and cohort studies, so one can either focus on the bivariate meta-analysis of the case-control studies or the trivariate meta-analysis of the cohort studies, as only the latter contains information on disease prevalence. In order to remedy this situation of wasting data we propose a hybrid copula mixed model via a combination of the bivariate and trivariate copula mixed model for the data from the case-control studies and cohort studies, respectively. Hence, this hybrid model can account for study design and also due to its generality can deal with dependence in the joint tails. We apply the proposed hybrid copula mixed model to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma.
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Lee, Young Hoon, Yang Woo Shin, and Dug Hee Moon. "Buffer Allocation Problem Using Meta-Model in an Automotive Body Shops with Mixed-model Production." Journal of the Korean Institute of Industrial Engineers 46, no. 3 (June 30, 2020): 296–308. http://dx.doi.org/10.7232/jkiie.2020.46.3.296.
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Yu, Tianwei. "Dimension reduction and mixed-effects model for microarray meta-analysis of cancer." Frontiers in Bioscience 13, no. 13 (2008): 2714. http://dx.doi.org/10.2741/2878.
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Singmann, Henrik, Karl Christoph Klauer, and David Kellen. "Intuitive Logic Revisited: New Data and a Bayesian Mixed Model Meta-Analysis." PLoS ONE 9, no. 4 (April 22, 2014): e94223. http://dx.doi.org/10.1371/journal.pone.0094223.
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Vogelgesang, Felicitas, Marc Dewey, and Peter Schlattmann. "The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R." Methods of Information in Medicine 57, no. 03 (May 2018): 111–19. http://dx.doi.org/10.3414/me17-01-0021.
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Summary Background: Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. Objectives: The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity – the two outcomes of interest in meta-analyses of diagnostic accuracy studies – utilizing random effects. Methods: Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). Results: The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. Conclusions: This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach.
Dissertations / Theses on the topic "Mixed meta-model"
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Herath, Shanaka, and Gunther Maier. "Informational efficiency of the real estate market: A meta-analysis." Hanyang Economic Research Institute, 2015. http://dx.doi.org/10.17256/jer.2015.20.2.001.
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The growing empirical literature testing informational efficiency of real estate markets uses data from various contexts and at different levels of aggregation. The results of these studies are mixed. We use a distinctive meta-analysis to examine whether some of these study characteristics and contexts lead to a significantly higher chance for identification of an efficient real estate market. The results generated through meta-regression suggest that use of stock market data and individual level data, rather than aggregate data, significantly improves the probability of a study concluding efficiency. Additionally, the findings neither provide support for the suspicion that the view of market efficiency has significantly changed over the years nor do they indicate a publication bias resulting from such a view. The statistical insignificance of other study characteristics suggests that the outcome concerning efficiency is a context-specific random manifestation for the most part. (authors' abstract)
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Ribbing, Jakob. "Covariate Model Building in Nonlinear Mixed Effects Models." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7923.
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Aroui, Karim. "Séquencement d’une ligne de montage multi-modèles : application à l’industrie du véhicule industriel." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAI029/document.
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Dans cette thèse, nous considérons le problème du séquencement sur une ligne de montage multi-modèles de véhicules industriels. Pour équilibrer au mieux la charge dynamique des opérateurs, la minimisation de la somme des retards à l’issue de chaque véhicule est proposée.Deux approches peuvent être utilisées pour optimiser le lissage de charge dans un problème de séquencement : l’utilisation directe des temps opératoires ou le respect de règles. La plupart des travaux appliqués à l’industrie automobile utilisent l’approche de respect de règles. Une originalité de ce travail est d’utiliser l’approche de la prise en compte directe des temps opératoires.L’étude de la littérature de ce problème a dévoilé deux lacunes dans les travaux précédents : l’essentiel des travaux modélisent un seul type d’opérateurs d’une part, et proposent des heuristiques ou des métaheuristiques pour résoudre ces problèmes, d’autre part. L’originalité de ce travail est de tester des méthodes exactes pour des instances industrielles et de modéliser le fonctionnement de trois différents types d’opérateurs spécifiques au cas industriel.Deux méthodes exactes sont développées : la programmation linéaire mixte et la programmation dynamique. Une étude expérimentale des facteurs de complexité sur des instances académiques des deux modèles est développée. Les modèles sont aussi testés sur des instances du cas d’étude.Par ailleurs, le problème est traité par deux méthodes approchées : une heuristique basée sur la programmation dynamique d’une part, et des métaheuristiques (algorithme génétique, recuit simulé et un couplage des deux) d’autre part. Les deux approches sont testées sur des instances académiques et des instances du cas d’étude.Ce travail a permis d’apporter une solution intéressante d’un point de vue industriel puisqu’il prend en compte les caractéristiques de la ligne de montage (opérateurs spécifiques) et améliore significativement la qualité du séquencement en un temps de calcul raisonnableIn this thesis, the problem of sequencing mixed model assembly lines (MMAL) is considered. Our goal is to determine the sequence of products to minimize the work overload. This problem is known as the mixed model assembly line sequencing problem with work overload minimization (MMSP-W). This work is based on an industrial case study of a truck assembly line.Two approaches can be used to minimize the work overload: the use of task operation times or the respect of sequencing rules. Most of the earlier works applied in car industry use the latter approach. The originality of this work is to employ the task operation times for the generation of the product sequence in a MMAL.The literature review has highlighted two main gaps in previous works: most of the papers consider a single type of operators, and propose heuristics or metaheuristics to solve the problem. The originality of this work is to test exact methods for industrial case instances and to model three different types of operators.Two exact methods are developed: the mixed integer linear programming and dynamic programming. The models are tested on industrial case study instances. An experimental study is developed for both approaches in order to understand the complexity factors.Moreover, the problem is treated by two approximate methods: a heuristic based on dynamic programming and metaheuristics (genetic algorithm, simulated annealing and a hybrid method based on both genetic algorithm and simulated annealing). All approaches are tested on academic instances and on real data from the industrial case study
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Cuesta, Ramirez Jhouben Janyk. "Optimization of a computationally expensive simulator with quantitative and qualitative inputs." Thesis, Lyon, 2022. http://www.theses.fr/2022LYSEM010.
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Dans cette thèse, les problèmes mixtes couteux sont abordés par le biais de processus gaussiens où les variables discrètes sont relaxées en variables latentes continues. L'espace continu est plus facilement exploité par les techniques classiques d'optimisation bayésienne que ne le serait un espace mixte. Les variables discrètes sont récupérées soit après l'optimisation continue, soit simultanément avec une contrainte supplémentaire de compatibilité continue-discrète qui est traitée avec des lagrangiens augmentés. Plusieurs implémentations possibles de ces optimiseurs mixtes bayésiens sont comparées. En particulier, la reformulation du problème avec des variables latentes continues est mise en concurrence avec des recherches travaillant directement dans l'espace mixte. Parmi les algorithmes impliquant des variables latentes et un lagrangien augmenté, une attention particulière est consacrée aux multiplicateurs de lagrange pour lesquels des techniques d'estimation locale et globale sont étudiées. Les comparaisons sont basées sur l'optimisation répétée de trois fonctions analytiques et sur une application mécanique concernant la conception d'une poutre. Une étude supplémentaire pour l'application d'une stratégie d'optimisation mixte proposée dans le domaine de l'auto-calibrage mixte est faite. Cette analyse s'inspire d'une application de quantification des radionucléides, qui définit une fonction inverse spécifique nécessitant l'étude de ses multiples propriétés dans le scenario continu. une proposition de différentes stratégies déterministes et bayésiennes a été faite en vue d'une définition complète dans un contexte de variables mixtesIn this thesis, costly mixed problems are approached through gaussian processes where the discrete variables are relaxed into continuous latent variables. the continuous space is more easily harvested by classical bayesian optimization techniques than a mixed space would. discrete variables are recovered either subsequently to the continuous optimization, or simultaneously with an additional continuous-discrete compatibility constraint that is handled with augmented lagrangians. several possible implementations of such bayesian mixed optimizers are compared. in particular, the reformulation of the problem with continuous latent variables is put in competition with searches working directly in the mixed space. among the algorithms involving latent variables and an augmented lagrangian, a particular attention is devoted to the lagrange multipliers for which a local and a global estimation techniques are studied. the comparisons are based on the repeated optimization of three analytical functions and a mechanical application regarding a beam design. an additional study for applying a proposed mixed optimization strategy in the field of mixed self-calibration is made. this analysis was inspired in an application in radionuclide quantification, which defined an specific inverse function that required the study of its multiple properties in the continuous scenario. a proposition of different deterministic and bayesian strategies was made towards a complete definition in a mixed variable setup
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Proença, Sara Isabel Azevedo. "Impact assessment of energy and climate policies : a hybrid botton-up general equilibrium model (HyBGem) for Portugal." Doctoral thesis, Instituto Superior de Economia e Gestão, 2013. http://hdl.handle.net/10400.5/6126.
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Doutoramento em EconomiaClimate change mitigation and the imperative of a new sustainable energy paradigm are among the greatest challenges facing the world today, and they are high on the priority list of policy makers as well as within the scientific community. In this context significant efforts are being made in the design and implementation of energy and carbon mitigation policies at both European and national level. Evidence of this can be seen in the recent adoption by the EU of an integrated climate and energy policy that setts ambitious binding targets to be achieved by 2020 – known as the 20-20-20 targets of the EU Climate and Energy Package. Undoubtedly, the cost of these policies can be substantially reduced if a comprehensive impact assessment is made of the most efficient and cost-effective policy measures and technological options. Policy impact assessment therefore plays an important role in supporting the energy and climate decision-making process. This is the context of and motivation for the research presented in this thesis. The first part of the thesis, the conceptual framework, describes the development of the Hybrid Bottom-up General Equilibrium Model (HyBGEM) for Portugal, as a decision-support tool to assist national policy makers in conducting energy and climate policy analysis. HyBGEM is a single integrated, multi-sector, hybrid top-down/bottom-up general equilibrium E3 model formulated as a mixed complementarity problem. The second part of the thesis, the empirical analysis, provides an impact assessment of Portugal’s 2020 energy-climate policy targets under the EU Climate and Energy Package commitments, based on the HyBGEM model and the baseline projections previously developed. Five policy scenarios have been modelled and simulated to evaluate the economic, environmental and technological impacts on Portugal of complying with its individual 2020 carbon emissions and renewable energy targets. Furthermore, insights are gained into how these targets interact with each other, what are the most efficient and cost-effective policy options, and how alternative pathways affect the extent of policy-induced effects. The numerical analysis reveals that Portugal’s 2020 energy-climate targets can be achieved without significant compliance costs. A major challenge for policy makers is to promote an effective decarbonisation of the electricity generation sector through renewable-based technologies. There is evidence that the compliance costs of Portugal’s low carbon target in 2020 are significantly higher than the costs of achieving the national RES-E target, given that imposing carbon emissions constraints and subsidising renewable electricity generation via a feed-in tariffs scheme both have a similar impact on economy-wide emissions. This result suggests that the most cost-effective policy option to achieve the national energy-climate targets is to promote renewable power generation technologies, recommending that policy makers should proceed with the mechanisms that support it. The transition to a ‘greener’ economy is thus central to the ongoing fight against climate change. There is also evidence that emission market segmentation as imposed by the current EU-ETS creates substantial excess costs compared to uniform emissions pricing through a comprehensive cap-and-trade system. The economic argument on counterproductive overlapping regulation is not corroborated by the findings. Furthermore, there is no potential for a double dividend arising from environmental tax reforms. To conclude, the results highlight the critical importance of market distortions and revenue-recycling schemes, together with baseline projections in policy impact assessment.
A mitigação das alterações climáticas e o imperativo de um novo paradigma energético sustentável estão entre os maiores desafios que o mundo de hoje enfrenta, surgindo no topo da lista de prioridades quer dos decisores políticos quer da comunidade científica. Neste contexto, têm sido envidados esforços significativos na conceção e aplicação de políticas energéticas e de mitigação de carbono, tanto a nível europeu como nacional. A recente adoção de uma política integrada da UE em matéria de clima e energia, com objetivos ambiciosos a serem alcançados até 2020 – os denominados objetivos 20-20-20 do Pacote Clima-Energia da UE, é prova disso. Não há dúvida de que o custo destas políticas pode ser substancialmente reduzido se for feita uma avaliação global das medidas e das opções tecnológicas mais eficientes e com melhor relação custo-eficácia. A avaliação de impacto das políticas desempenha assim um papel importante no apoio à tomada de decisão em matéria energética e climática. São estes o contexto e a motivação para a investigação apresentada nesta tese. A primeira parte da tese, referente à estrutura conceptual, descreve o desenvolvimento do modelo HyBGEM – Hybrid Bottom-up General Equilibrium Model, concebido para Portugal. Trata-se de uma ferramenta de apoio à decisão em matéria de políticas de energia-clima. O HyBGEM é um modelo E3 de equilíbrio geral, com uma estrutura híbrida top-down/bottom-up integrada, multi-setorial e formulado como um problema de complementaridade mista. A segunda parte da tese, referente à análise empírica, apresenta uma avaliação de impacto das políticas de energia-clima para Portugal no quadro dos compromissos assumidos no Pacote Clima-Energia da UE, com base no modelo HyBGEM e em projeções de base previamente construídas. Foram modelados e simulados cinco cenários de política para avaliar os impactos económicos, ambientais e tecnológicos do cumprimento das metas nacionais traçadas para 2020 em matéria de limitação de emissões de carbono e promoção das energias renováveis. Avalia-se também o modo como estes objetivos interagem entre si, quais são as opções de política mais eficientes e custo-eficazes, e em que medida opções alternativas influenciam a magnitude dos impactos. A análise numérica revela que as metas energia-clima 2020 para Portugal podem ser alcançadas sem incorrer em custos de cumprimento significativos. O desafio fundamental que se coloca aos decisores políticos consiste em impulsionar a descarbonização do setor de produção de energia elétrica através de tecnologias de energia renovável. Existe evidência de que os custos de cumprimento da meta de redução de carbono são significativamente mais elevados que os custos de cumprimento da meta de FER-E, sendo que a imposição de restrições às emissões e a subsidiação da produção de eletricidade a partir de fontes de energia renovável (regime de tarifas feed-in) têm um impacto semelhante sobre o total de emissões. Este resultado sugere que a promoção das tecnologias de base renovável no sistema energético nacional é a opção com melhor relação custo-eficácia para a concretização dos objetivos nacionais energia-clima para 2020, instando os decisores políticos a prosseguir com os mecanismos de apoio existentes. A transição para uma economia mais ‘verde’ afigura-se assim fundamental no combate em curso contra as alterações climáticas. A análise revela também que a segmentação do mercado de emissões imposta pelo atual CELE gera custos adicionais substanciais quando comparada com um sistema de direitos de emissão uniforme. O argumento económico de que a sobreposição de regulamentação é contraproducente não é corroborado pelos resultados. A expectativa de um duplo dividendo decorrente das reformas fiscais em matéria ambiental não foi confirmada. Os resultados destacam ainda a importância crítica das distorções de mercado, dos sistemas de reciclagem de receitas e das projeções de base, para a avaliação de impacto das políticas.
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Aljafary, Michelle. "Accounting for potential nonlinearity between catch and effort using meta-analysis and applying GLM and GLMM to fishing data from deployments of fixed and mobile gear." 2016. http://hdl.handle.net/1993/31208.
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My thesis examines nonlinearity between catch and effort. I use a meta-analysis of published literature and generalized linear mixed-effects models (GLMM) on both fixed and mobile gear fisheries of Atlantic Canada. The meta-analysis examines the proportionality of catch to effort using the slope of the reduced major axis (RMA) log-log regression, which accounts for “errors-in-variables”. The GLMMs explored proportionality while accounting for variation among fishing vessels. Both analyses found evidence for disproportionality between catch and effort. Catch that increases disproportionally to effort could result from either facilitation or recruitment of effort into the fishery. Catch increases that are less than proportional are expected from competitive interactions among fishers or gear saturation. The GLMM also revealed that the level of aggregation (by set, trip, monthly, or annually) can affect the apparent proportionality between catch and effort. In general, catch and effort should not be considered to be proportional.May 2016
Book chapters on the topic "Mixed meta-model"
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"Meta-analysis Model." In Mixed Models, 247–90. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471728438.ch5.
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"Meta-Analysis Model." In Mixed Models, 245–90. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118651537.ch5.
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Interian, Alejandro, Ariana Prawda, Daniel B. Fishman, and William M. Buerger. "Motivational Enhancement Therapy for Increasing Antidepressant Medication Adherence and Decreasing Clinical Depression Among Adult Latinos." In Case Studies Within Psychotherapy Trials, 256–362. Oxford University Press, 2016. http://dx.doi.org/10.1093/med:psych/9780199344635.003.0009.
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Case Studies Within Psychotherapy Trials: Integrating Qualitative and Quantitative Methods presents a specific, mixed-methods approach, called the “Cases Within Trials” (CWT) model, to psychotherapy research, combining the results from a randomized clinical trial (RCT), from case studies drawn from the RCT, and a synthesis of the two types of knowledge. Chapter 6 of the book applies this model to a study of the application of a three-session, individual, “motivational interviewing” therapy—specifically labeled “motivational enhancement therapy for antidepressants” (META). META was employed for treating disadvantaged, predominantly Spanish-speaking Latinos with depression. Finding META plus routine individual psychiatric therapy based in a community mental health center (CMHC) to be statistically and substantially superior to the CMHC-therapy-only condition, the authors then analyze and compare the positive-outcome case of Lupe, the mixed-outcome case of Ana, and the negative-outcome case of Maria, all drawn from the META condition.
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Ma, Qingxiong, and Liping Liu. "The Technology Acceptance Model." In Advances in End User Computing, 112–28. IGI Global, 2005. http://dx.doi.org/10.4018/978-1-59140-474-3.ch006.
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The technology acceptance model proposes that perceived ease of use and perceived usefulness predict the acceptance of information technology. Since its inception, the model has been tested with various applications in tens of studies and has become a most widely applied model of user acceptance and usage. Nevertheless, the reported findings on the model are mixed in terms of statistical significance, direction, and magnitude. In this study, we conducted a meta-analysis based on 26 selected empirical studies in order to synthesize the empirical evidence. The results suggest that both the correlation between usefulness and acceptance and between usefulness and ease of use are somewhat strong. However, the relationship between ease of use and acceptance is weak, and its significance does not pass the fail-safe test.
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Ma, Qingxiong, and Liping Liu. "The Technology Acceptance Model." In End-User Computing, 1088–100. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-945-8.ch079.
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The technology acceptance model proposes that perceived ease of use and perceived usefulness predict the acceptance of information technology. Since its inception, the model has been tested with various applications in tens of studies and has become the most widely applied model of user acceptance and usage. Nevertheless, the reported findings on the model are mixed in terms of statistical significance, direction, and magnitude. In this study, we conducted a meta-analysis based on 26 selected empirical studies in order to synthesize the empirical evidence. The results suggest that both the correlation between usefulness and acceptance, and that between usefulness and ease of use are somewhat strong. However, the relationship between ease of use and acceptance is weak, and its significance does not pass the fail-safe test.
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Yaghin, Reza Ghasemy, Hadi Mosadegh, and S. M. T. Fatemi Ghomi. "Differential Return on Investment Optimization." In Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems, 189–211. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2944-6.ch009.
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A two-echelon supply chain is studied that involves a retailer who faces demand from two or more market segments and enable to set different prices and marketing expenditures and a supplier who desires to find optimal number of shipments through an integrated system. A new mixed-integer non-linear fractional programming (MINLFP) model is developed. In order to solve the resultant MINLFP model, the constrained non-linear programming model is reformulated as an unconstrained one using penalty terms. Two meta-heuristics, namely simulated annealing (SA) and imperialist competitive algorithm (ICA), are applied to solve the relaxed unconstrained model. Numerical results show that ICA can reach better solutions in comparison with SA. However, SA has the ability of providing more robust solutions which are converged to a good solution. The chapter concludes with superiority of SA.
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"Meta-Analysis on Individual Participant Data." In Applied Mixed Model Analysis, 166–78. Cambridge University Press, 2019. http://dx.doi.org/10.1017/9781108635660.012.
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"Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future." In Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future, edited by Randall M. Petermrman, Brian J. Pyper, Franz J. Mueter, Steven L. Haeseker, Zhenming Su, and Brigitte Dorner. American Fisheries Society, 2009. http://dx.doi.org/10.47886/9781934874097.ch8.
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<em>Abstract.</em>—Past attempts to improve population models of Pacific salmon <em>Oncorhynchus </em>spp. by adding indices of freshwater or marine conditions have shown mixed success. To increase chances that such models will remain reliable over the long term, we suggest adding only environmental covariates that have a spatial scale of positive correlation among monitoring locations similar to, or greater than, that of the salmon variables that scientists are trying to explain. To illustrate this approach, we analyzed spawner and recruit data for 120 populations (stocks) of pink <em>O. gorbuscha</em>, chum <em>O. keta</em>, and sockeye <em>O. nerka </em>salmon from Washington, British Columbia, and Alaska. Salmon productivity of a given species was positively correlated across stocks at a spatial scale of about 500–800 km. Compared to upwelling and sea-surface salinity, summer sea-surface temperature (SST) showed a more appropriate spatial scale of positive covariation for explaining variation in salmon productivity, and was a significant explanatory variable when added to both single-stock and multi-stock spawner-recruit models. This result suggests that future models of these salmon populations should possibly include stock-specific, summer SST. To further explore our understanding of salmon population dynamics, we developed 24 alternative stock–recruitment models. We compared these models in three ways: (1) their fit to all past data, (2) their ability to forecast recruitment, and (3) their performance inside an “operating model,” which included components for dynamics of the natural ecological system, stock assessments based on simulated sampling of data, regulation-setting based on those assessments, and variation in implementing those regulations (reflecting noncompliance or other sources of outcome uncertainty). We also compared single-stock models with multi-stock models (meta-analyses). The latter led to more precise estimates of the effects of SST on log<sub>e</sub>(recruits/spawner) and greater accuracy of preseason forecasts for some stocks. Analyses with the operating model show that reducing outcome uncertainty should be a top management priority.
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Jelen, Jonatan, Billy Brocato, Thomas M. Schmidt, and Stuart S. Gold. "In Search of a Star Trek Affective State." In Organizational Integration of Enterprise Systems and Resources, 42–59. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1764-3.ch003.
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The authors’ meta-analysis showed that leadership studies have ignored pioneering research into the heuristic tools people employ that affect decision-making and, subsequently, judgments regarding effective group performance in organizational settings. The chapter suggests a postmodern model superseding the modernist perspectives whose theoretical grounding remain mired in Frederick Taylor’s (1911) scientific management theories. The authors’ meta-analysis identified salient characteristics found in the selected leadership research, allowing for a disambiguation of the transformational and charismatic leadership operational traits. The meta-analysis comprised selected research studies from 1999 to 2008, and revealed distinctive intrapersonal (5 organizational referents) and interpersonal (5 social identity/normative referents) icons that inform emergent leader and follower behaviors. The chapter proposes a postmodern evaluation matrix to reveal the structural biases and modernist conceptual ambiguities tied to the leader-worker dyadic in varying organizational contexts. The findings suggest that leadership researchers should consider complex behavioral decision-making processes that result in emergent group performances instead of focusing on a leader’s ephemeral behavioral traits. A postmodern approach also helps leadership researchers identify a group’s performance on a continuum that would demonstrate their willingness to act in a way that tests individual limits, stretches group boundaries, and exceeds company goals, what the authors term a Star Trek Affective State.
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Rajak, Sonu, P. Parthiban, and R. Dhanalakshmi. "Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm." In Supply Chain and Logistics Management, 726–49. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0945-6.ch034.
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This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illustrate the model developed and concluding remarks are made regarding the results.
Conference papers on the topic "Mixed meta-model"
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Rao, Yunqing, Kunpeng Wang, and Mengchang Wang. "Modeling impact of product variety on performance in mixed-model assembly system: An artificial neural network meta-modeling approach." In EM). IEEE, 2010. http://dx.doi.org/10.1109/ieem.2010.5674187.
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Xu, Weili, Khee Poh Lam, and Omer T. Karaguzel. "Using an Adaptive Meta-Model Evolutionary Algorithm for Mixed-Integer Type Building Design Optimization for Building Simulation 2017 Conference." In 2017 Building Simulation Conference. IBPSA, 2017. http://dx.doi.org/10.26868/25222708.2017.328.
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Tian, Yiran, and Yanfeng Shen. "Improved Nonlinear Ultrasonic Guided Wave Damage Detection Using a Bandgap Meta-Surface." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86222.
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In this study, a kind of meta-surface was designed for the improvement of nonlinear ultrasonic guided wave detection by creating bandgaps. It is composed of aluminum alloy cylinders arranged in a periodic pattern bounded on an aluminum plate. By artificially adjusting the height of the cylinders, the meta-surface can open up bandgaps over desired frequency ranges. Guided waves within the bandgap cannot propagate through the meta-surface and will be mechanically filtered out. To perform non-destructive evaluation (NDE) of structural components with fatigue cracks, the guided waves generated by a piezoelectric wafer active sensor (PWAS) propagate into the structure, interact with the crack, acquire nonlinear features, and are picked up by the receiver PWAS. In an ideal case, the waves excited by the transmitter PWAS should only contain signals at the fundamental frequency. However, due to the inherent nonlinearity of the electronic instrument, the generated signals are often mixed with weak superharmonic components. And these inherent higher harmonic signals will adversely affect the identifiability of nonlinear characteristics in the sensing signals. The bandgap mechanism and the wave vector dispersion relationship of the meta-surface are investigated using the modal analysis of a finite element model (FEM) by treating a unit structural cell with the Bloch-Floquet boundary condition. In this way, the meta-surface is carefully designed to obtain bandgaps at the desired frequency ranges. Then, a FEM harmonic analysis of a chain of unit cells is performed to further explore the bandgap efficiency. Finally, a coupled field transient dynamic FEM is constructed to simulate the improved nonlinear ultrasonic guided wave active sensing procedure with the bandgap meta-surface. The proposed method possesses great potential for future SHM and NDE applications.
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Zhao, Xiangxue, Zhimin Xi, Hongyi Xu, and Ren-Jye Yang. "Model Bias Characterization Considering Discrete and Continuous Design Variables." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60109.
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Model bias can be normally modeled as a regression model to predict potential model errors in the design space with sufficient training data sets. Typically, only continuous design variables are considered since the regression model is mainly designed for response approximation in a continuous space. In reality, many engineering problems have discrete design variables mixed with continuous design variables. Although the regression model of the model bias can still approximate the model errors in various design/operation conditions, accuracy of the bias model degrades quickly with the increase of the discrete design variables. This paper proposes an effective model bias modeling strategy to better approximate the potential model errors in the design/operation space. The essential idea is to firstly determine an optimal base model from all combination models derived from discrete design variables, then allocate majority of the bias training samples to this base model, and build relationships between the base model and other combination models. Two engineering examples are used to demonstrate that the proposed approach possesses better bias modeling accuracy compared to the traditional regression modeling approach. Furthermore, it is shown that bias modeling combined with the baseline simulation model can possess higher model accuracy compared to the direct meta-modeling approach using the same amount of training data sets.
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Maddulapalli, Anil Kumar, Parameshwaran S. Iyer, and N. R. Srinivasa Raghavan. "Selecting and Optimizing a Regulation Compliant Robust Vehicle Portfolio Mix: An Approach and a Case Study." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70832.
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Our goal is to select a robust vehicle portfolio mix and optimize its design attributes such that contribution margin is maximized while being regulation compliant under varying fuel prices. Compliance to regulation is measured in terms of the Corporate Average Fuel Economy or CAFE. We formulate this vehicle portfolio optimization problem as a mixed integer non-linear programming problem, both under static and varying fuel price scenarios. We demonstrate our approach using a case study in which an in-house market simulator is employed for incorporating consumer preferences in portfolio decisions. This market simulator uses real-time preferences from tens of thousands of shoppers and captures preference heterogeneity using different Logit coefficients for each shopper and hence is computationally expensive. Also, it does not explicitly model the influence of fuel price in predicting demand. To overcome these issues and to facilitate portfolio optimization we use meta-models of the market simulator. Our results show that while remaining regulation compliant it is also possible to achieve significant improvement in the portfolio’s contribution margin. In some scenarios, the improvements in contribution margin are more than 40% when compared to the traditional approach of using expert judgment to decide the portfolio mix.
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Sun, Yidan, Guiyuan Jiang, Siew Kei Lam, and Peilan He. "Predicting Traffic Congestion Evolution: A Deep Meta Learning Approach." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/417.
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Many efforts are devoted to predicting congestion evolution using propagation patterns that are mined from historical traffic data. However, the prediction quality is limited to the intrinsic properties that are present in the mined patterns. In addition, these mined patterns frequently fail to sufficiently capture many realistic characteristics of true congestion evolution (e.g., asymmetric transitivity, local proximity). In this paper, we propose a representation learning framework to characterize and predict congestion evolution between any pair of road segments (connected via single or multiple paths). Specifically, we build dynamic attributed networks (DAN) to incorporate both dynamic and static impact factors while preserving dynamic topological structures. We propose a Deep Meta Learning Model (DMLM) for learning representations of road segments which support accurate prediction of congestion evolution. DMLM relies on matrix factorization techniques and meta-LSTM modules to exploit temporal correlations at multiple scales, and employ meta-Attention modules to merge heterogeneous features while learning the time-varying impacts of both dynamic and static features. Compared to all state-of-the-art methods, our framework achieves significantly better prediction performance on two congestion evolution behaviors (propagation and decay) when evaluated using real-world dataset.
Reports on the topic "Mixed meta-model"
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Jiménez-Parra, José Francisco, Sixto González-Víllora, and Alfonso Valero-Valenzuela. The evolution of the Teaching Personal and Social Responsibility from a contextual to a transcontextual model. A systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0031.
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Review question / Objective: The aim of this research was to identify and analyze the advances produced during the last 6 years in intervention studies based on the Model of Personal and Social Responsibility (TPSR) both in the subject of physical education and in any other area of knowledge within the school context. To conduct this study, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed (Moher et al., 2015) and the question was elaborated in the PICO format: (P) Participants or Problem (eg children, adolescents, Elementary, secondary, country), (I) Intervention (eg units, lessons, quantitative, qualitative or mixed research), (C) Comparators (“Teaching Personal and Social Responsibility”, “Education”), and (O) Outcomes (eg personal and social responsibility, motivation, prosocial behaviors, basic psychological needs, perception of students and teachers).