Relevant bibliographies by topics / Data driven model

Academic literature on the topic 'Data driven model'

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Published: 4 June 2021
Last updated: 9 March 2023

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Journal articles on the topic "Data driven model"

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Cho, Kunhee, Joahun Kim, Hyeongcheol Lee, Seung-Han You, and Wanki Cho. "Data-driven Based Accuracy Improvement for Vehicle Lateral Model." Transaction of the Korean Society of Automotive Engineers 30, no. 2 (February 1, 2022): 133–42. http://dx.doi.org/10.7467/ksae.2022.30.2.133.

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Eggersmann, R., T. Kirchdoerfer, S. Reese, L. Stainier, and M. Ortiz. "Model-Free Data-Driven inelasticity." Computer Methods in Applied Mechanics and Engineering 350 (June 2019): 81–99. http://dx.doi.org/10.1016/j.cma.2019.02.016.

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Hewitt, Mike, and Emma Frejinger. "Data-driven optimization model customization." European Journal of Operational Research 287, no. 2 (December 2020): 438–51. http://dx.doi.org/10.1016/j.ejor.2020.05.010.

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Matusik, Wojciech, Hanspeter Pfister, Matt Brand, and Leonard McMillan. "A data-driven reflectance model." ACM Transactions on Graphics 22, no. 3 (July 2003): 759–69. http://dx.doi.org/10.1145/882262.882343.

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Sorescu, Alina. "Data-Driven Business Model Innovation." Journal of Product Innovation Management 34, no. 5 (June 27, 2017): 691–96. http://dx.doi.org/10.1111/jpim.12398.

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Le-Tien, Thuong, Hanh Phan-Xuan, Thuy Nguyen-Chinh, and Thien Do-Tieu. "Image Forgery Detection: A Low Computational-Cost and Effective Data-Driven Model." International Journal of Machine Learning and Computing 9, no. 2 (April 2019): 181–88. http://dx.doi.org/10.18178/ijmlc.2019.9.2.784.

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Cuzzocrea, Alfredo, Jose Norberto Mazon, Juan Trujillo, and Jose Zubcoff. "Model-driven data mining engineering: from solution-driven implementations to 'composable' conceptual data mining models." International Journal of Data Mining, Modelling and Management 3, no. 3 (2011): 217. http://dx.doi.org/10.1504/ijdmmm.2011.041808.

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Wang, Nannan, Mingrui Zhu, Jie Li, Bin Song, and Zan Li. "Data-driven vs. model-driven: Fast face sketch synthesis." Neurocomputing 257 (September 2017): 214–21. http://dx.doi.org/10.1016/j.neucom.2016.07.071.

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CHE-JUNG, CHANG, LI GUIPING, GUO JIANHONG, and YU KUN-PENG. "Data-Driven Forecasting Model for Small Data Sets." ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH 54, no. 4/2020 (December 15, 2020): 217–29. http://dx.doi.org/10.24818/18423264/54.4.20.14.

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Forgione, Marco, Xavier Bombois, and Paul M. J. Van den Hof. "Data-driven model improvement for model-based control." Automatica 52 (February 2015): 118–24. http://dx.doi.org/10.1016/j.automatica.2014.11.006.

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Dissertations / Theses on the topic "Data driven model"

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Aboulsamh, Mohammed A. "Model-driven data migration." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:44ddbf8b-a6a0-4830-baeb-13b2c746802f.

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Information systems often hold data of considerable value. Their continuing development or maintenance will often necessitate evolution of the system and migration of the data from one version to the next: a process that may be expensive, time-consuming, and prone to error. That such a process remains a source of challenges, is recognized by both academia and industry. In current practice, data migration is often considered only in the later stages of development, leaving critical data to be transformed and loaded by hand-written scripts, long after the design process has been completed. The advent of model-driven engineering offers an opportunity to consider the question of information system evolution and data migration earlier in the development process. A precise account of the proposed changes to an existing system model can be used to predict the consequences for existing data, and to generate the necessary data migration implementation. This dissertation shows how automatic data migration can be achieved by extending the definition of a data modeling language to include model level operations, each of which corresponds to the addition, modification, or deletion of a model component. Using the Unified Modeling Language (UML) notation as an example, we show how the specification of these operations may be translated into an abstract program in the Abstract Machine Notation (AMN), employed in the B-method, and then formally checked for consistency and applicability prior to translation into a concrete programming notation, such as Structured Query Language (SQL).
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Matusik, Wojciech 1973. "A data-driven reflectance model." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87454.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
"September 2003."
Includes bibliographical references (leaves 112-115).
I present a data-driven model for isotropic bidirectional reflectance distribution functions (BRDFs) based on acquired reflectance data. Instead of using analytic reflectance models, each BRDF is represented as a dense set of measurements. This representation allows interpolation and extrapolation in the space of acquired BRDFs to create new BRDFs. Each acquired BRDF is treated as a single high-dimensional vector taken from the space of all possible BRDFs. Both linear (subspace) and non-linear (manifold) dimensionality reduction tools are applied in an effort to discover a lower-dimensional representation that characterizes the acquired BRDFs. To complete the model, users are provided with the means for defining perceptually meaningful parametrizations that allow them to navigate in the reduced-dimension BRDF space. On the low-dimensional manifold, movement along these directions produces novel, but valid, BRDFs. By analyzing a large collection of reflectance data, I also derive two novel reflectance sampling procedures that require fewer total measurements than standard uniform sampling approaches. Using densely sampled measurements the general surface reflectance function is analyzed to determine the local signal variation at each point in the function's domain. Wavelet analysis is used to derive a common basis for all of the acquired reflectance functions, as well as a non-uniform sampling pattern that corresponds to all non-zero wavelet coefficients. Second, I show that the reflectance of an arbitrary material can be represented as a linear combination of the surface reflectance functions. Furthermore, this analysis specifies a reduced set of sampling points that permits the robust estimation of the coefficients of this linear combination.
(cont.) These procedures dramatically shorten the acquisition time for isotropic reflectance measurements.
by Wojciech Matusik.
Ph.D.
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Safie, Lily Suryani Binti. "A software component model that is both control-driven and data-driven." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/a-software-component-model-that-is-both-controldriven-and-datadriven(ce21c34b-7257-4b8f-aa79-f6456b49a3a0).html.

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A software component model is the cornerstone of any Component-based Software Development (CBSD) methodology. Such a model defines the modelling elements for constructing software systems. In software system modelling, it is necessary to capture the three elements of a system's behaviour: (i) control (ii) computation and (iii) data. Within a system, computations are performed according to the flow of control or the flow of data, depending on whether computations are control-driven or data-driven. Computations are function evaluations, assignments, etc., which transform data when invoked by control or data flow. Therefore a component model should be able to model control flow, data flow as well as computations. Current component models all model computations, but beside computations tend to model either control flow only or data flow only, but not both. In this thesis, we present a new component model which can model both control flow and data flow. It contains modelling elements that capture control flow and data flow explicitly. Furthermore, the modelling of control flow is separate from that of data flow; this enables the modelling of both control-driven and data-driven computations. The feasibility of the model is shown by means of an implementation of the model, in the form of a prototype tool. The usefulness of the model is then demonstrated for a specific domain, the embedded systems domain, as well as a generic domain. For the embedded systems domain, unlike current models, our model can be used to construct systems that are both control-driven and data-driven. In a generic domain, our model can be used to construct domain models, by constructing control flows and data flows which together define a domain model.
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Elbekai, Ali Sayeh. "Generic model for application driven XML data processing." Thesis, Northumbria University, 2006. http://nrl.northumbria.ac.uk/55/.

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XML technology has emerged during recent years as a popular choice for representing and exchanging semi-structured data on the Web. It integrates seamlessly with web-based applications. If data is stored and represented as XML documents, then it should be possible to query the contents of these documents in order to extract, synthesize and analyze their contents. This thesis for experimental study of Web architecture for data processing is based on semantic mapping of XML Schema. The thesis involves complex methods and tools for specification, algorithmic transformation and online processing of semi-structured data over the Web in XML format with persistent storage into relational databases. The main focus of the research is preserving the structure of original data for data reconciliation during database updates and also to combine different technologies for XML data processing such as storing (SQL), transformation (XSL Processors), presenting (HTML), querying (XQUERY) and transporting (Web services) using a common framework, which is both theoretically and technologically well grounded. The experimental implementation of the discussed architecture requires a Web server (Apache), Java container (Tomcat) and object-relational DBMS (Oracle 9) equipped with Java engine and corresponding libraries for parsing and transformation of XML data (Xerces and Xalan). Furthermore the central idea behind the research is to use a single theoretical model of the data to be processed by the system (XML algebra) controlled by one standard metalanguage specification (XML Schema) for solving a class of problems (generic architecture). The proposed work combines theoretical novelty and technological advancement in the field of Internet computing. This thesis will introduce a generic approach since both our model (XML algebra) and our problem solver (the architecture of the integrated system) are XML Schema- driven. Starting with the XML Schema of the data, we first develop domain-specific XML algebra suitable for data processing of the specific data and then use it for implementing the main offline components of the system for data processing.
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Boruvka, Audrey. "Data-driven estimation for Aalen's additive risk model." Thesis, Kingston, Ont. : [s.n.], 2007. http://hdl.handle.net/1974/489.

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Syed, Mofazzal. "Data driven modelling for environmental water management." Thesis, Cardiff University, 2007. http://orca.cf.ac.uk/54592/.

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Management of water quality is generally based on physically-based equations or hypotheses describing the behaviour of water bodies. In recent years models built on the basis of the availability of larger amounts of collected data are gaining popularity. This modelling approach can be called data driven modelling. Observational data represent specific knowledge, whereas a hypothesis represents a generalization of this knowledge that implies and characterizes all such observational data. Traditionally deterministic numerical models have been used for predicting flow and water quality processes in inland and coastal basins. These models generally take a long time to run and cannot be used as on-line decision support tools, thereby enabling imminent threats to public health risk and flooding etc. to be predicted. In contrast, Data driven models are data intensive and there are some limitations in this approach. The extrapolation capability of data driven methods are a matter of conjecture. Furthermore, the extensive data required for building a data driven model can be time and resource consuming or for the case predicting the impact of a future development then the data is unlikely to exist. The main objective of the study was to develop an integrated approach for rapid prediction of bathing water quality in estuarine and coastal waters. Faecal Coliforms (FC) were used as a water quality indicator and two of the most popular data mining techniques, namely, Genetic Programming (GP) and Artificial Neural Networks (ANNs) were used to predict the FC levels in a pilot basin. In order to provide enough data for training and testing the neural networks, a calibrated hydrodynamic and water quality model was used to generate input data for the neural networks. A novel non-linear data analysis technique, called the Gamma Test, was used to determine the data noise level and the number of data points required for developing smooth neural network models. Details are given of the data driven models, numerical models and the Gamma Test. Details are also given of a series experiments being undertaken to test data driven model performance for a different number of input parameters and time lags. The response time of the receiving water quality to the input boundary conditions obtained from the hydrodynamic model has been shown to be a useful knowledge for developing accurate and efficient neural networks. It is known that a natural phenomenon like bacterial decay is affected by a whole host of parameters which can not be captured accurately using solely the deterministic models. Therefore, the data-driven approach has been investigated using field survey data collected in Cardiff Bay to investigate the relationship between bacterial decay and other parameters. Both of the GP and ANN models gave similar, if not better, predictions of the field data in comparison with the deterministic model, with the added benefit of almost instant prediction of the bacterial levels for this recreational water body. The models have also been investigated using idealised and controlled laboratory data for the velocity distributions along compound channel reaches with idealised rods have located on the floodplain to replicate large vegetation (such as mangrove trees).
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Bugtai, Nilo T. "Fixturing information models in data model-driven product design and manufacture." Thesis, Loughborough University, 2002. https://dspace.lboro.ac.uk/2134/34654.

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In order to ensure effective decisions are made at each stage in the design and manufacture process, it is important that software tools should provide sufficient information to support the decision making of both designers and manufacturing engineers. This requirement can be applied to fixturing where research to date has typically focused on narrow functional support issues in fixture design and planning. The research reported in this thesis has explored how models of fixturing information can be defined, within an integrated information environment, and utilised across product design as well as manufacture. The work has focused on the definition of fixturing information within the context of a wide-ranging model that can capture the full capability of a manufacturing facility.
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Kis, Filip. "Prototyping with Data : Opportunistic Development of Data-Driven Interactive Applications." Doctoral thesis, KTH, Medieteknik och interaktionsdesign, MID, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-196851.

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There is a growing amount of digital information available from Open-Data initiatives, Internet-of-Things technologies, and web APIs in general. At the same time, an increasing amount of technology in our lives is creating a desire to take advantage of the generated data for personal or professional interests. Building interactive applications that would address this desire is challenging since it requires advanced engineering skills that are normally reserved for professional software developers. However, more and more interactive applications are prototyped outside of enterprise environments, in more opportunistic settings. For example, knowledge workers apply end-user development techniques to solve their tasks, or groups of friends get together for a weekend hackathon in the hope of becoming the next big startup. This thesis focuses on how to design prototyping tools that support opportunistic development of interactive applications that take advantage of the growing amount of available data. In particular, the goal of this thesis is to understand what are the current challenges of prototyping with data and to identify important qualities of tools addressing these challenges. To accomplish this, declarative development tools were explored, while keeping focus on what data and interaction the application should afford rather than on how they should be implemented (programmed). The work presented in this thesis was carried out as an iterative process which started with a design exploration of Model-based UI Development, followed by observations of prototyping practices through a series of hackathon events and an iterative design of Endev – a prototyping tool for data-driven web applications. Formative evaluations of Endev were conducted with programmers and interaction designers.  The main results of this thesis are the identified challenges for prototyping with data and the key qualities required of prototyping tools that aim to address these challenges. The identified key qualities that lower the threshold for prototyping with data are: declarative prototyping, familiar and setup-free environment, and support tools. Qualities that raise the ceiling for what can be prototyped are: support for heterogeneous data and for advanced look and feel.
Mer och mer digital information görs tillgänglig på olika sätt, t.ex. via öppna data-initiativ, Sakernas internet och API:er. Med en ökande teknikanvändning så skapas även ett intresse för att använda denna data i olika sammanhang, både privat och professionellt. Att bygga interaktiva applikationer som adresserar dessa intressen är en utmaning då det kräver avancerade ingenjörskunskaper, vilket man vanligtvis endast hittar hos professionella programmerare. Sam­tidigt byggs allt fler interaktiva applikationer utanför företagsmiljöer, i mer opportunistiska sammanhang. Detta kan till exempel vara kunskapsarbetare som använder sig av s.k. anveckling (eng. end-user development) för att lösa en uppgift, eller kompisar som träffas en helg för att hålla ett hackaton med hopp om att bli nästa framgångsrika startup-företag. Den här avhandlingen fokuserar på hur prototypverktyg kan utformas för att stödja utveckling av interaktiva applikationer i sådana opportunistiska sammanhang, som utnyttjar den ökande mängden av tillgänglig data. Målet med arbetet som presenteras i den här avhandlingen har varit att förstå utmaningarna som det innebär att använda data i prototyparbete och att identifiera viktiga kvalitéer för de verktyg som ska kunna hantera detta. För att uppnå detta mål har verktyg för deklarativ programmering utforskats med ett fokus kring vilken data och interaktion en applikationen ska erbjuda snarare än hur den ska implementeras. Arbetet som presenteras i den här avhandlingen har genomförts som en iterativ process, med en startpunkt i en utforskning av modellbaserad gränssnittsutveckling, vilket sedan följdes av observationer av prototyparbete i praktiken genom en serie hackathon och en iterativ design av Endev, som är ett prototypverktyg för att skapa datadrivna webbapplikationer. Formativa utvärderingar av Endev har utförts med programmerare och interaktionsdesigners. De viktigaste resultaten av den här avhandlingen är de utmaningar som har identifierats kring hur man skapar prototyper och de kvalitéer som krävs av prototypverktyg som ska adressera dessa utmaningar. De identifierade kvalitéerna som sänker trösklarna för att inkludera data i prototyper är: deklarativt prototyparbete, välbekanta och installationsfria miljöer, och supportverktyg. Kvalitéer som höjer taket för vad som kan göras i en prototyp är: stöd för olika typer av data och för avancerad “look and feel”.
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Malatesta, William, and Clay Fink. "MEASUREMENT-CENTRIC DATA MODEL FOR INSTRUMENTATION CONFIGURATION." International Foundation for Telemetering, 2007. http://hdl.handle.net/10150/604525.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada
CTEIP has launched the integrated Network Enhanced Telemetry (iNET) project to foster advances in networking and telemetry technology to meet emerging needs of major test programs. In the past these programs have been constrained by vendor proprietary equipment configuration utilities that force a significant learning curve on the part of instrumentation personnel to understand hardware idiosyncrasies and require significant human interaction and manipulation of data to be exchanged between different components of the end-to-end test system. This paper describes an ongoing effort to develop a measurement-centric data model of airborne data acquisition systems. The motivation for developing such a model is to facilitate hardware and software interoperability and to alleviate the need for vendor-specific knowledge on the part of the instrumentation engineer. This goal is driven by requirements derived from scenarios collected by the iNET program. This approach also holds the promise of decreased human interaction with and manipulation of data to be exchanged between system components.
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Koc, Birgul. "Numerical Analysis for Data-Driven Reduced Order Model Closures." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103202.

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This dissertation contains work that addresses both theoretical and numerical aspects of reduced order models (ROMs). In an under-resolved regime, the classical Galerkin reduced order model (G-ROM) fails to yield accurate approximations. Thus, we propose a new ROM, the data-driven variational multiscale ROM (DD-VMS-ROM) built by adding a closure term to the G-ROM, aiming to increase the numerical accuracy of the ROM approximation without decreasing the computational efficiency. The closure term is constructed based on the variational multiscale framework. To model the closure term, we use data-driven modeling. In other words, by using the available data, we find ROM operators that approximate the closure term. To present the closure term's effect on the ROMs, we numerically compare the DD-VMS-ROM with other standard ROMs. In numerical experiments, we show that the DD-VMS-ROM is significantly more accurate than the standard ROMs. Furthermore, to understand the closure term's physical role, we present a theoretical and numerical investigation of the closure term's role in long-time integration. We theoretically prove and numerically show that there is energy exchange from the most energetic modes to the least energetic modes in closure terms in a long time averaging. One of the promising contributions of this dissertation is providing the numerical analysis of the data-driven closure model, which has not been studied before. At both the theoretical and the numerical levels, we investigate what conditions guarantee that the small difference between the data-driven closure model and the full order model (FOM) closure term implies that the approximated solution is close to the FOM solution. In other words, we perform theoretical and numerical investigations to show that the data-driven model is verifiable. Apart from studying the ROM closure problem, we also investigate the setting in which the G-ROM converges optimality. We explore the ROM error bounds' optimality by considering the difference quotients (DQs). We theoretically prove and numerically illustrate that both the ROM projection error and the ROM error are suboptimal without the DQs, and optimal if the DQs are used.
Doctor of Philosophy
In many realistic applications, obtaining an accurate approximation to a given problem can require a tremendous number of degrees of freedom. Solving these large systems of equations can take days or even weeks on standard computational platforms. Thus, lower-dimensional models, i.e., reduced order models (ROMs), are often used instead. The ROMs are computationally efficient and accurate when the underlying system has dominant and recurrent spatial structures. Our contribution to reduced order modeling is adding a data-driven correction term, which carries important information and yields better ROM approximations. This dissertation's theoretical and numerical results show that the new ROM equipped with a closure term yields more accurate approximations than the standard ROM.
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Books on the topic "Data driven model"

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Bjornar, Solhaug, and Stølen Ketil, eds. Model-driven risk analysis: The CORAS approach. Berlin: Springer, 2010.

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From Model-Based to Data-Driven Discrete-Time Iterative Learning Control. [New York, N.Y.?]: [publisher not identified], 2019.

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editor, Margaria-Steffen Tiziana 1964, ed. Process design for natural scientists: An agile model-driven approach. Heidelberg: Springer, 2014.

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Halle, Barbara Von. The decision model: A framework for business logic and business-driven SOA. Boca Raton: Auerbach, 2010.

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Halle, Barbara Von. The decision model: A framework for business logic and business-driven SOA. Boca Raton: Auerbach, 2010.

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1946-, Goldberg Larry, ed. The decision model: A framework for business logic and business-driven SOA. Boca Raton: Auerbach, 2010.

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Jörges, Sven. Construction and Evolution of Code Generators: A Model-Driven and Service-Oriented Approach. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Andreas, Prinz, Reed Rick, and Reed Jeanne 1948-, eds. SDL 2005: Model driven : 12th international SDL Forum, Grimstad, Norway, June 20-23, 2005 : proceedings. Berlin: Springer, 2005.

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International Research Forum 2007: [Enterprise 2.0, the service grid, user-driven innovation, business model transformation. New York, NY: Evolved Technologist Press, 2008.

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Weber, Alan. Data-driven business models. Mason, Ohio: Thomson, 2005.

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Book chapters on the topic "Data driven model"

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Jianhong, Wang, Ricardo A. Ramirez-Mendoza, and Ruben Morales-Menendez. "Data Driven Model Predictive Control." In Data Driven Strategies, 8–53. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003160700-2.

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Aboulsamh, Mohammed, Edward Crichton, Jim Davies, and James Welch. "Model-Driven Data Migration." In Lecture Notes in Computer Science, 285–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16385-2_35.

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Jianhong, Wang, Ricardo A. Ramirez-Mendoza, and Ruben Morales-Menendez. "Data Driven Model Validation for Closed Loop System." In Data Driven Strategies, 108–46. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003160700-4.

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Rashedi, Jonas. "Process Model for Data Management." In The Data-driven Organization, 39–73. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20604-7_4.

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Pan, Yue, Guotong Xie, Li Ma, Yang Yang, ZhaoMing Qiu, and Juhnyoung Lee. "Model-Driven Ontology Engineering." In Journal on Data Semantics VII, 57–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890591_3.

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Precup, Radu-Emil, Raul-Cristian Roman, and Ali Safaei. "Hybrid Model-Free and Model-Free Adaptive Fuzzy Controllers." In Data-Driven Model-Free Controllers, 259–342. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003143444-7.

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André, Pascal, and Mohammed El Amin Tebib. "More Automation in Model Driven Development." In Model and Data Engineering, 75–83. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78428-7_7.

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Tillmann, George. "Building the Logical Data Model." In Usage-Driven Database Design, 45–67. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2722-0_4.

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Remesan, Renji, and Jimson Mathew. "Model Data Selection and Data Pre-processing Approaches." In Hydrological Data Driven Modelling, 41–70. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09235-5_3.

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Precup, Radu-Emil, Raul-Cristian Roman, and Ali Safaei. "Model-Free Adaptive Controllers." In Data-Driven Model-Free Controllers, 167–209. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003143444-5.

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Conference papers on the topic "Data driven model"

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Milward, David. "Model Driven Data Management in Healthcare." In 7th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007391101050116.

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Milward, David. "Model Driven Data Management in Healthcare." In 7th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007391101070118.

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Tembine, Hamidou. "Data-driven vs model-driven imitative learning." In 2017 IEEE 6th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2017. http://dx.doi.org/10.1109/ddcls.2017.8067719.

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Koupil, Pavel, Sebastián Hricko, and Irena Holubová. "Schema inference for multi-model data." 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/10.1145/3550355.3552400.

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Rajbahadur, Gopi Krishnan, Gustavo Ansaldi Oliva, Ahmed E. Hassan, and Juergen Dingel. "Pitfalls Analyzer: Quality Control for Model-Driven Data Science Pipelines." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2019. http://dx.doi.org/10.1109/models.2019.00-19.

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"A Model-driven Process for Data Transformation of Heterogeneous Data." In International Conference on Model-Driven Engineering and Software Development. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004221901770181.

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Kollar, Jan, Peter Vaclavik, and L'ubomir Wassermann. "Data-driven executable language model." In 2009 International Multiconference on Computer Science and Information Technology (IMCSIT). IEEE, 2009. http://dx.doi.org/10.1109/imcsit.2009.5352766.

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Zhang, Xiao-guang. "Model Driven Data Service Development." In 2008 IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2008. http://dx.doi.org/10.1109/icnsc.2008.4525489.

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Merlo, Luca. "The Data Driven Flavour Model." In 40th International Conference on High Energy physics. Trieste, Italy: Sissa Medialab, 2021. http://dx.doi.org/10.22323/1.390.0401.

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Matusik, Wojciech, Hanspeter Pfister, Matt Brand, and Leonard McMillan. "A data-driven reflectance model." In ACM SIGGRAPH 2003 Papers. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/1201775.882343.

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Reports on the topic "Data driven model"

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Syeda-Mahmood, Tanveer F. Data and Model-Driven Selection Using Color Regions. Fort Belvoir, VA: Defense Technical Information Center, February 1992. http://dx.doi.org/10.21236/ada260101.

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Tanveer, S., and F. Mahmood. Data and Model-Driven Selection using Parallel-Line Groups. Fort Belvoir, VA: Defense Technical Information Center, May 1993. http://dx.doi.org/10.21236/ada293889.

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Howe, Bill. Gridfields: Model-Driven Data Transformation in the Physical Sciences. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2667.

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D'Elia, Marta, Stewart Silling, Yue Yu, and Huaiqian You. A data-driven peridynamic continuum model for upscaling molecular dynamics. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1821529.

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Meidani, Hadi, and Amir Kazemi. Data-Driven Computational Fluid Dynamics Model for Predicting Drag Forces on Truck Platoons. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-036.

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Abstract:
Fuel-consumption reduction in the truck industry is significantly beneficial to both energy economy and the environment. Although estimation of drag forces is required to quantify fuel consumption of trucks, computational fluid dynamics (CFD) to meet this need is expensive. Data-driven surrogate models are developed to mitigate this concern and are promising for capturing the dynamics of large systems such as truck platoons. In this work, we aim to develop a surrogate-based fluid dynamics model that can be used to optimize the configuration of trucks in a robust way, considering various uncertainties such as random truck geometries, variable truck speed, random wind direction, and wind magnitude. Once trained, such a surrogate-based model can be readily employed for platoon-routing problems or the study of pavement performance.
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Vesselinov, Velimir V., Dylan R. Harp, and Danny Katzman. Model-driven decision support for monitoring network design based on analysis of data and model uncertainties: methods and applications. Office of Scientific and Technical Information (OSTI), January 2013. http://dx.doi.org/10.2172/1059873.

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Frick, Glendon M., Peter Caffrey, and William Hoppel. Analysis of the RED Aerosol Data Set by the NRL Aerosol Model Driven by COAMPS. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada629742.

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Crews, John H., Ralph C. Smith, Kyle M. Pender, Jennifer C. Hannen, and Gregory D. Buckner. Data-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory Alloys. Fort Belvoir, VA: Defense Technical Information Center, November 2011. http://dx.doi.org/10.21236/ada556936.

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Wu, S. T., and A. H. Wang. Development of a Data Driven Three-dimensional Magnetohydrodynamic Model With Radiation Effects to Study Photosphere-Coronal Coupling. Fort Belvoir, VA: Defense Technical Information Center, February 2011. http://dx.doi.org/10.21236/ada563642.

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Reno, Matthew, Logan Blakely, Rodrigo Trevizan, Bethany Pena, Matthew Lave, Joseph Azzolini, Jubair Yusuf, et al. IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Final Report. Office of Scientific and Technical Information (OSTI), January 2022. http://dx.doi.org/10.2172/1855058.

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