Academic literature on the topic 'Exploration models'

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Journal articles on the topic "Exploration models"

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Phillips, Thelma M. "Exploration of Theoretical Models." Nursing Science Quarterly 27, no. 4 (September 22, 2014): 308–14. http://dx.doi.org/10.1177/0894318414546409.

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Wimsatt, William C. "Models and experiments? An exploration." Biology & Philosophy 30, no. 2 (July 10, 2014): 293–98. http://dx.doi.org/10.1007/s10539-014-9451-1.

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Doganova, Liliana. "Economic models as exploration devices." Journal of Economic Methodology 22, no. 2 (April 3, 2015): 249–53. http://dx.doi.org/10.1080/1350178x.2015.1037544.

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Rylskiу, Ilya. "Lidar virtual models for seismic exploration." InterCarto. InterGIS 27, no. 1 (2021): 304–16. http://dx.doi.org/10.35595/2414-9179-2021-1-27-304-316.

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Seismic exploration is important for development of new fields and the resumption of production at old areas of oil production. These works involve studying of underground geological structures using seismic profiling and seismotomography methods. In fact, detailed information about the territory is necessary for almost every participant in the process—to find the optimal routes for movement on terrain, to optimize the volume of forest felling on profiles, for georeferencing and checking coordinate measurements at points, etc. The availability of spatial data is also important for increasing the level of safety and trouble-free operation during work. One of possible solutions is to perform field surveys using aerial photography and airborne laser scanning, followed creation of virtual models based on them with instrumentation adapted to the specifics of these works. Modern GIS, with all their development, has number of disadvantages. It is difficult to use GIS by non-specialists; full-featured GIS are expensive, and free solutions has limited analysis functionality and can’t make good 3D visualizations, it is difficult to protect spatial information from unauthorized copying. These problems can be solved without using classic GIS packages. Instead, it is proposed to use virtual environments closed from editing and access to the original data. Test area of 69 km2 in the Khanty-Mansiysk Autonomous Okrug was selected for testing virtual modeling technologies. LIDAR and aerial photography datasets were obtained, and subsequent processing of the resulting was done, forming highly-detailed virtual environment. The article discusses the main features and functionality of this model.
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de Souza e Silva, Edmundo, and Pedro Mejiá Ochoa. "State space exploration in Markov models." ACM SIGMETRICS Performance Evaluation Review 20, no. 1 (June 1992): 152–66. http://dx.doi.org/10.1145/149439.133100.

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Otto, Gordon H. "Statistical Models for Optimizing Mineral Exploration." Technometrics 32, no. 4 (November 1990): 460–61. http://dx.doi.org/10.1080/00401706.1990.10484750.

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Roman, Gruia-Catalin, and Jamie Payton. "A principled exploration of coordination models." Theoretical Computer Science 336, no. 2-3 (May 2005): 367–401. http://dx.doi.org/10.1016/j.tcs.2004.11.012.

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Beyer, Uwe, and Frank Śmieja. "Data exploration with reflective adaptive models." Computational Statistics & Data Analysis 22, no. 2 (July 1996): 193–211. http://dx.doi.org/10.1016/0167-9473(95)00048-8.

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Thompson, David R., Alberto Candela, David S. Wettergreen, Eldar Noe Dobrea, Gregg A. Swayze, Roger N. Clark, and Rebecca Greenberger. "Spatial Spectroscopic Models for Remote Exploration." Astrobiology 18, no. 7 (July 2018): 934–54. http://dx.doi.org/10.1089/ast.2017.1782.

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Łucki, Zbigniew, and Zbigniew Szkutnik. "Petroleum exploration models—Estimation and applications." Mathematical Geology 21, no. 5 (July 1989): 495–512. http://dx.doi.org/10.1007/bf00894665.

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Dissertations / Theses on the topic "Exploration models"

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Gross, Joshua. "An exploration of stochastic models." Kansas State University, 2014. http://hdl.handle.net/2097/17656.

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Master of Science
Department of Mathematics
Nathan Albin
The term stochastic is defined as having a random probability distribution or pattern that may be analyzed statistically but may not be predicted precisely. A stochastic model attempts to estimate outcomes while allowing a random variation in one or more inputs over time. These models are used across a number of fields from gene expression in biology, to stock, asset, and insurance analysis in finance. In this thesis, we will build up the basic probability theory required to make an ``optimal estimate", as well as construct the stochastic integral. This information will then allow us to introduce stochastic differential equations, along with our overall model. We will conclude with the "optimal estimator", the Kalman Filter, along with an example of its application.
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Carter, Faye Isobel. "Exploration of siblings' explanatory models of autism." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1581479771&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Kamphans, Thomas. "Models and algorithms for online exploration and search." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980408121.

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Gosch, Aron. "Exploration of 5G Traffic Models using Machine Learning." Thesis, Linköpings universitet, Databas och informationsteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-168160.

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The Internet is a major communication tool that handles massive information exchanges, sees a rapidly increasing usage, and offers an increasingly wide variety of services.   In addition to these trends, the services themselves have highly varying quality of service (QoS), requirements and the network providers must take into account the frequent releases of new network standards like 5G. This has resulted in a significant need for new theoretical models that can capture different network traffic characteristics. Such models are important both for understanding the existing traffic in networks, and to generate better synthetic traffic workloads that can be used to evaluate future generations of network solutions using realistic workload patterns under a broad range of assumptions and based on how the popularity of existing and future application classes may change over time. To better meet these changes, new flexible methods are required. In this thesis, a new framework aimed towards analyzing large quantities of traffic data is developed and used to discover key characteristics of application behavior for IP network traffic. Traffic models are created by breaking down IP log traffic data into different abstraction layers with descriptive values. The aggregated statistics are then clustered using the K-means algorithm, which results in groups with closely related behaviors. Lastly, the model is evaluated with cluster analysis and three different machine learning algorithms to classify the network behavior of traffic flows. From the analysis framework a set of observed traffic models with distinct behaviors are derived that may be used as building blocks for traffic simulations in the future. Based on the framework we have seen that machine learning achieve high performance on the classification of network traffic, with a Multilayer Perceptron getting the best results. Furthermore, the study has produced a set of ten traffic models that have been demonstrated to be able to reconstruct traffic for various network entities.

Due to COVID-19 the presentation was performed over ZOOM.

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Havercroft, William G. "Exploration of marginal structural models for survival outcomes." Thesis, University of Bristol, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.684750.

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A marginal structural model parameterises the distribution of an outcome given a treatment intervention, where such a distribution is the fundamental probabilistic representation of the causal effect of treatment on the outcome. Causal inference methods are designed to consistently estimate aspects of these causal distributions, in the presence of interference from non-causal associations which typically occur in observational data. One such method, which involves the application of inverse probability of treatment weights, directly targets the parameters of marginal structural models. The asymptotic properties and practical applicability of this method are well established, but little attention has been paid to its finite-sample performance. This is because simulating data from known distributions which are entirely suitable for such investigations generally presents a significant challenge, especially in scenarios where the outcome is survival time. We illuminate these issues, and propose and implement certain solutions, considering separately the cases of static (pre-determined) and dynamic (tailored) treatment interventions. In so doing, we explore both theoretical and practical aspects of marginal structural models for survival outcomes, and the associated inference method.
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Mulchahey, Kenneth E. "Exploration of Complexities for Migration of Software-Licensing Models." Thesis, Capella University, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13806407.

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Some independent software vendors might not endure the reduction in revenue and increased costs associated when they switch software license models. The lack of identified and prioritized complexities might lead to potential increased revenue loss or prevent small and medium-sized independent software vendors within the United States from migrating from perpetual software licensing to subscription-based models. The purpose of this qualitative case study was to explore, document, and describe organizational complexities and their prioritization in contributing to the failure or success of software license model migration. The research questions for this qualitative case study included a Primary Research Question: What complexities can senior management of small and medium-sized independent software vendors (ISV) encounter when migrating from a perpetual license model to a subscription-based licensing model? Supporting Research Question 1: What is the prioritization of the complexities determined to be a factor in the migration of software licensing models? Supporting Research Question 2: How do identifying and prioritizing complexities affect decision-making to mitigate potential initial revenue loss? For this study, eight managers were recruited from a small to medium sized independent software vendor. Specifically, participants in the sample were managers who have worked within the software industry for at least four years, had knowledge of the company’s existing software license model, and were involved in the consideration of migrating from a perpetual license model to a subscription-based licensing model. The data collection methods for this research were face-to-face interviews, a focus group, and direct observations. The multi-criteria decision analysis theory and diffusion of influence theory served as the conceptual framework for this research. The framework provided a model for software vendor executives to identify and prioritize complexities and reduce the initial loss of revenue during license migration. Eight themes emerged: financial, go-to-market, infrastructure, reorganization, security, training, and unknown strategy. There was a consistency between the themes and literature. The data was consistent with the multi-criteria decision and diffusion of influence theories. The results indicated four key findings: support functions were less aware of complexities, no evidence of a clear strategic plan was present, the most significant complexity anticipated was the go-to-market complexity, and there was a direct effect on decision-making in identifying and prioritizing complexities. Exploring and understanding the totality of complexities an independent software vendor may encounter, the prioritization of those complexities, and adjusting decision-making to compensate for those complexities, while establishing and following a communicated strategic plan may significantly reduce the potential for financial loss, increase market positioning and competitive advantage. The results and limitations may provide areas for future research. Future studies should seek to conduct similar studies with multiple independent software vendors to provide additional levels of validation and reliability. Such studies should include independent software vendors who have successfully and unsuccessfully migrated license models.

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Gaier, Adam. "Accelerating Evolutionary Design Exploration with Predictive and Generative Models." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0087.

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L'optimisation joue un rôle essentiel dans la conception industrielle, mais ne se limite pas à la minimisation d'une simple fonction, comme le coût ou la résistance. Ces outils sont également utilisés dans les phases conceptuelles, pour mieux comprendre ce qui est possible. Pour soutenir cette exploration, nous nous concentrons sur les algorithmes de diversité de qualité (QD), qui produisent des ensembles de solutions variées et performantes. Ces techniques nécessitent souvent l'évaluation de millions de solutions, ce qui les rend peu pratiques dans les cas de conception. Dans cette thèse, nous proposons des méthodes pour améliorer radicalement l'efficacité des données de la QD avec l'apprentissage machine, permettant son application à la conception. Dans notre première contribution, nous développons une méthode de modélisation des performances des réseaux neuronaux évolués utilisés pour le contrôle et la conception. Les structures de ces réseaux se développent et changent, ce qui les rend difficiles à modéliser - mais grâce à une nouvelle méthode, nous sommes en mesure d'estimer leurs performances en fonction de leur hérédité, améliorant ainsi l'efficacité des données à plusieurs reprises. Dans notre deuxième contribution, nous combinons l'optimisation basée sur un modèle avec MAP-Elites, un algorithme QD. Un modèle de performance est créé à partir de modèles connus, et MAP-Elites crée un nouvel ensemble de modèles en utilisant cette approximation. Un sous-ensemble de ces conceptions est évalué pour améliorer le modèle, et le processus se répète. Nous montrons que cette approche améliore l'efficacité de MAP-Elites par des ordres de grandeur. Notre troisième contribution intègre des modèles générateurs dans MAP-Elites pour apprendre des codages spécifiques à un domaine. Un auto-codeur variationnel est formé sur les solutions produites par MAP-Elites, capturant la "recette" commune pour une haute performance. Ce codage appris peut ensuite être réutilisé par d'autres algorithmes pour une optimisation rapide, y compris MAP-Elites. Tout au long de cette thèse, bien que notre vision se concentre sur la conception, nous examinons les applications dans d'autres domaines, comme la robotique. Ces avancées ne sont pas exclusives à la conception, mais servent de travail de base à l'intégration de la DQ et de l'apprentissage machine
Optimization plays an essential role in industrial design, but is not limited to minimization of a simple function, such as cost or strength. These tools are also used in conceptual phases, to better understand what is possible. To support this exploration we focus on Quality Diversity (QD) algorithms, which produce sets of varied, high performing solutions. These techniques often require the evaluation of millions of solutions -- making them impractical in design cases. In this thesis we propose methods to radically improve the data-efficiency of QD with machine learning, enabling its application to design. In our first contribution, we develop a method of modeling the performance of evolved neural networks used for control and design. The structures of these networks grow and change, making them difficult to model -- but with a new method we are able to estimate their performance based on their heredity, improving data-efficiency by several times. In our second contribution we combine model-based optimization with MAP-Elites, a QD algorithm. A model of performance is created from known designs, and MAP-Elites creates a new set of designs using this approximation. A subset of these designs are the evaluated to improve the model, and the process repeats. We show that this approach improves the efficiency of MAP-Elites by orders of magnitude. Our third contribution integrates generative models into MAP-Elites to learn domain specific encodings. A variational autoencoder is trained on the solutions produced by MAP-Elites, capturing the common “recipe” for high performance. This learned encoding can then be reused by other algorithms for rapid optimization, including MAP-Elites. Throughout this thesis, though the focus of our vision is design, we examine applications in other fields, such as robotics. These advances are not exclusive to design, but serve as foundational work on the integration of QD and machine learning
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Garcia, Gomez David. "Exploration of customer churn routes using machine learning probabilistic models." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/144660.

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The ongoing processes of globalization and deregulation are changing the competitive framework in the majority of economic sectors. The appearance of new competitors and technologies entails a sharp increase in competition and a growing preoccupation among service providing companies with creating stronger bonds with customers. Many of these companies are shifting resources away from the goal of capturing new customers and are instead focusing on retaining existing ones. In this context, anticipating the customer¿s intention to abandon, a phenomenon also known as churn, and facilitating the launch of retention-focused actions represent clear elements of competitive advantage. Data mining, as applied to market surveyed information, can provide assistance to churn management processes. In this thesis, we mine real market data for churn analysis, placing a strong emphasis on the applicability and interpretability of the results. Statistical Machine Learning models for simultaneous data clustering and visualization lay the foundations for the analyses, which yield an interpretable segmentation of the surveyed markets. To achieve interpretability, much attention is paid to the intuitive visualization of the experimental results. Given that the modelling techniques under consideration are nonlinear in nature, this represents a non-trivial challenge. Newly developed techniques for data visualization in nonlinear latent models are presented. They are inspired in geographical representation methods and suited to both static and dynamic data representation.
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Kamphans, Tom [Verfasser]. "Models and Algorithms for Online Exploration and Search / Tom Kamphans." Aachen : Shaker, 2011. http://d-nb.info/1098040260/34.

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Ost, Luciano Copello. "Abstract models of NoC-based MPSoCs for design space exploration." Pontifícia Universidade Católica do Rio Grande do Sul, 2010. http://hdl.handle.net/10923/1663.

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NoC-based MPSoCs can provide massive computing power on a single chip, achieving hundreds of billions of operations per second by employing dozens of processing cores that communicate over a packet-switched network at a rate that exceeds 100 Tbps. Such devices can support the convergence of several appliances (e. g. HDTV, multiple wireless communication standards, media players, gaming) due to their comparatively high performance, flexibility and power efficiency. Due to the vast design space alternatives, evaluating the NoC-based MPSoCs at lower abstraction levels does not provide the required support to find out the most efficient NoC architecture considering the performance constraints (e. g. latency, power) of a given application at early design process stages. Thus, NoC-based MPSoCs design requires simple and accurate high level models in order to achieve precise performance results, of each design alternative, in an acceptable design time. In this context, the present Thesis has two main contributions: (i) development of abstract NoC models, providing accurate performance evaluation; and (ii) integration of the proposed models into a model-based design flow, allowing the design space exploration of NoC-based MPSoCs at early stages of the design flow.
MPSoCs baseados em NoCs podem fornecer alto desempenho em um único circuito integrado, atingindo centenas de bilhões de operações por segundo através do emprego de múltiplos elementos de processamento que se comunicam através de uma NoC operando a uma freqüência que excede 100 Tbps. Tais dispositivos podem suportar a execução simultânea de múltiplas aplicações (e. g. HDTV, múltiplos padrões de comunicação sem fio, tocadores multimídia, jogos), devido a características como alto desempenho, flexibilidade e eficiência em termos de consumo de energia. Devido a quantidade de alternativas inerentes ao grande espaço de projeto, a avaliação de MPSoCs baseados em NoCs em baixo níveis de abstração não prove o suporte necessário para encontrar a melhor arquitetura para a NoC considerando métricas de desempenho (e. g. latência, potência) de uma dada aplicação nas fases iniciais de projeto. Dessa forma, o projeto de MPSoCs baseados em NoCs requer modelos simples e precisos em alto nível de abstração, os quais possam gerar resultados precisos de desempenho, de cada alternativa de projeto, em um tempo de projeto razoável. Neste contexto, a presente Tese tem duas contribuições principais: (i) desenvolvimento de modelos de NoC abstratos, e (ii) integração dos modelos propostos dentro de um fluxo de projeto baseado em modelos, permitindo assim a exploração do espaço de projeto de MPSoCs baseados em NoCs nas fases iniciais do fluxo projeto.
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Books on the topic "Exploration models"

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G, De Geoffroy J., ed. Statistical models for optimizing mineral exploration. New York: Plenum Press, 1987.

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Wignall, T. K., and J. De Geoffroy. Statistical Models for Optimizing Mineral Exploration. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1861-3.

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Sandstone depositional models for exploration for fossil fuels. 3rd ed. Boston: International Human Resources Development Corp., 1985.

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Obstfeld, Maurice. Dynamic seigniorage theory: An exploration. Cambridge, Mass: National Bureau of Economic Research, 1989.

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Obstfeld, Maurice. Dynamic seigniorage theory: An exploration. London: Centre for Economic Policy Research, 1991.

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Comin, Diego. An exploration of technology diffusion. Cambridge, Mass: National Bureau of Economic Research, 2006.

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Comin, Diego. An exploration of technology diffusion. Cambridge, MA: National Bureau of Economic Research, 2006.

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Geoffroy, J. G. De. Designing optimalstrategies for mineral exploration. New York: Plenum, 1985.

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Odada, J. E. O. An aggregate consumption function for Namibia: An empirical exploration. Windhoek, Namibia: University of Namibia, Multi-disciplinary Research Consultancy Centre, Social Sciences Division, 2000.

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Exploration and innovation in design: Towards a computational model. New York: Springer-Verlag, 1991.

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Book chapters on the topic "Exploration models"

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Zhou, Xiang Sean, Yong Rui, and Thomas S. Huang. "Probabilistic Local Structure Models." In Exploration of Visual Data, 39–52. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0497-9_4.

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Laake, Andreas. "Digital Relief Models." In Remote Sensing for Hydrocarbon Exploration, 53–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73319-3_4.

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Stetter, Martin. "Computational Models of Early Vision." In Exploration of Cortical Function, 189–206. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0430-5_9.

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Hall, Greg. "Conceptual models in gold exploration." In Mineral Deposit Research: Meeting the Global Challenge, 1461–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/3-540-27946-6_371.

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Tedesco, Steven A. "Grids, Surveys, Models, and Economics." In Surface Geochemistry in Petroleum Exploration, 192–200. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2660-5_13.

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Colman, T. B., J. D. Cornwell, D. G. Jones, J. A. Plant, K. Smith, and A. S. D. Walker. "Exploration Criteria." In Metallogenic models and exploration criteria for buried carbonate-hosted ore deposits—a multidisciplinary study in eastern England, 135–37. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-7184-5_9.

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Solis, C. Vanessa, P. Ana León, and Oscar Pastor Lopez. "Genomic Databases Exploration Using Conceptual Models." In Advances in Intelligent Systems and Computing, 83–96. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35740-5_6.

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Sinvhal, Amita, and Harsha Sinvhal. "Monte Carlo Models in Oil Exploration." In Seismic Modelling and Pattern Recognition in Oil Exploration, 11–32. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2570-3_2.

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Sinvhal, Amita, and Harsha Sinvhal. "Morkov Chain Models in Oil Exploration." In Seismic Modelling and Pattern Recognition in Oil Exploration, 33–61. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2570-3_3.

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Knorreck, Daniel, Ludovic Apvrille, and Renaud Pacalet. "Fast Simulation Techniques for Design Space Exploration." In Objects, Components, Models and Patterns, 308–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02571-6_18.

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Conference papers on the topic "Exploration models"

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Eder, Johannes, Andreas Bahya, Sebastian Voss, Alexandru Ipatiov, and Maged Khalil. "From Deployment to Platform Exploration." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3239372.3239385.

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Gogolla, Martin, Robert Clariso, Bran Selic, and Jordi Cabot. "Towards Facilitating the Exploration of Informal Concepts in Formal Modeling Tools." In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2021. http://dx.doi.org/10.1109/models-c53483.2021.00044.

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lacolina, Samuel A., Alessandro Soro, and Riccardo Scateni. "Natural exploration of 3D models." In the 9th ACM SIGCHI Italian Chapter International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2037296.2037326.

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Ross, Jordan A., Alexandr Murashkin, Jia Hui Liang, Michal Antkiewicz, and Krzysztof Czarnecki. "Synthesis and Exploration of Multi-level, Multi-perspective Architectures of Automotive Embedded Systems (SoSYM Abstract)." In 2017 ACM/IEEE 20th International Conference on Model-Driven Engineering Languages and Systems (MODELS). IEEE, 2017. http://dx.doi.org/10.1109/models.2017.38.

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Eder, Johannes. "Exploration of hardware topologies based on functions, variability and timing." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3270112.3275333.

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Ma'ayan, Dor, Shahar Maoz, and Roey Rozi. "Validating the correctness of reactive systems specifications through systematic exploration." In MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3550355.3552425.

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Schnober, Carsten, and Iryna Gurevych. "Combining Topic Models for Corpus Exploration." In CIKM'15: 24th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2809936.2809939.

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de Souza e Silva, Edmundo, and Pedro Mejiá Ochoa. "State space exploration in Markov models." In the 1992 ACM SIGMETRICS joint international conference. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/133057.133100.

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Ahn, Jae-wook, Peter Brusilovsky, Daqing He, Jonathan Grady, and Qi Li. "Personalized web exploration with task models." In Proceeding of the 17th international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1367497.1367499.

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Pilarski, Sebastian, Martin Staniszewski, Frederic Villeneuve, and Daniel Varro. "On Artificial Intelligence for Simulation and Design Space Exploration in Gas Turbine Design." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2019. http://dx.doi.org/10.1109/models-c.2019.00029.

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Reports on the topic "Exploration models"

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Hewett, J. Monte Carlo Exploration of Warped Higgsless Models. Office of Scientific and Technical Information (OSTI), July 2004. http://dx.doi.org/10.2172/827313.

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Peter, J. M., M. G. Gadd, D. Layton-Matthews, W. D. Goodfellow, S. E. Jackson, B. E. Taylor, and N. Johnson. Development of genetic and exploration models for hyper-enriched black shale (HEBS) deposits. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2017. http://dx.doi.org/10.4095/299622.

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Huang, Cheng, William E. Anderson, Charles L. Merkle, and Venkateswaran Sankaran. Exploration of POD-Galerkin Techniques for Developing Reduced Order Models of Reaction-Advection Equations. Fort Belvoir, VA: Defense Technical Information Center, April 2014. http://dx.doi.org/10.21236/ada611205.

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Caballero, Juan, Stephen McCamant, Adam Barth, and Dawn Song. Extracting Models of Security-Sensitive Operations using String-Enhanced White-Box Exploration on Binaries. Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada538848.

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Vollet, Justin. Capturing Peers', Teachers', and Parents' Joint Contributions to Students' Engagement: An Exploration of Models. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5658.

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Schmid, K., and K. Olschewski. Practical aspects and experience resulting from borehole models for gamma ray logging in uranium exploration. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/123601.

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Slack, J. F. Models for tourmalinite formation in the Middle Proterozoic Belt and Purcell supergroups (Rocky Mountains) and their exploration significance. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/184093.

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Glass, R. J., M. J. Nicholl, and V. C. Tidwell. Challenging and improving conceptual models for isothermal flow in unsaturated, fractured rock through exploration of small-scale processes. Office of Scientific and Technical Information (OSTI), July 1996. http://dx.doi.org/10.2172/266709.

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Stevenson, M., J. Coty, J. Stewart, T. Carlsen, and M. Callaham. Developing Terrestrial Trophic Models for Petroleum and Natural Gas Exploration and Production Sites: The Oklahoma Tallgrass Prairie Preserve Example. Office of Scientific and Technical Information (OSTI), January 2001. http://dx.doi.org/10.2172/15013280.

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Hinze, W. J., L. W. Braile, R. R. B. von Frese, E. G. Lidiak, R. E. Denison, G. R. Keller, R. F. Roy, C. A. Swanberg, C. L. V. Aiken, and P. Morgan. Exploration for hot dry rock geothermal resources in the Midcontinent USA. Hot dry rock conceptual models for exploration, HDR test site investigations, and the Illinois Deep Drill Hole Project. Volume 2. Office of Scientific and Technical Information (OSTI), February 1986. http://dx.doi.org/10.2172/5694937.

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