Relevant bibliographies by topics / Model reference

Academic literature on the topic 'Model reference'

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Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Model reference"

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Shiota, T., and H. Ohmori. "Variable Reference Model for Model Reference Adaptive Control System." IFAC-PapersOnLine 48, no. 14 (2015): 72–75. http://dx.doi.org/10.1016/j.ifacol.2015.09.436.

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Chow, Shui-Nee, and Yongfeng Li. "Model reference control for SIRS models." Discrete & Continuous Dynamical Systems - A 24, no. 3 (2009): 675–97. http://dx.doi.org/10.3934/dcds.2009.24.675.

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Sisson, Norwood. "Dialogue management reference model." ACM SIGCHI Bulletin 18, no. 2 (October 1986): 34–35. http://dx.doi.org/10.1145/15683.15687.

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LEE, BORE-KUEN, BOR-SEN CHEN, and YU-PING LIN. "Model reference deadbeat control." International Journal of Control 54, no. 5 (November 1991): 1217–31. http://dx.doi.org/10.1080/00207179108934206.

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Montagner, Jean-Paul, and Don L. Anderson. "Constrained reference mantle model." Physics of the Earth and Planetary Interiors 58, no. 2-3 (December 1989): 205–27. http://dx.doi.org/10.1016/0031-9201(89)90055-1.

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Su, Shi-jie, Yuan-yuan Zhu, Hai-rong Wang, and Chen Yun. "A method to construct a reference model for model reference adaptive control." Advances in Mechanical Engineering 11, no. 11 (November 2019): 168781401989045. http://dx.doi.org/10.1177/1687814019890455.

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Model reference adaptive control takes the output of a reference model as the target and ensures that the actual output is consistent with the target. In this scenario, the reference model determines the performance of the control system. Constructing a reference model with specific performance is challenging, and most researchers construct the reference model by experience. As alternative frameworks, we propose two novel reference model construction methods, namely, zero-pole method and frequency response method. The zero-pole method establishes a nonlinear optimization model to ensure that the added zeros and poles are as far away from the imaginary axis as possible. In the case where this cannot be done, the frequency response method matches the system frequency response of the reference model and the given model to the extent possible using a nonlinear optimization model. Experimental results are presented to confirm that both methods can construct a reference model based on a given transfer function. Deviations in response between the reference models constructed using the two methods and the given model are compared, and the reasons for higher accuracy of the frequency response method are discussed.
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Salahou, Mohamed Khaled, Raphinos Tackmore Murava, and Xiu Ju Zhang. "Reference Evapotranspiration Models." Applied Mechanics and Materials 256-259 (December 2012): 2444–53. http://dx.doi.org/10.4028/www.scientific.net/amm.256-259.2444.

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This paper will examine the concept of evapotranspiration (ET) in more detail and provide more details into the concept of reference evapotranspiration (ETo) and of the measurement and estimation of ETo. Studies of ET models usually involve the comparison of a single model in different climates, different model types in the same location, or model output to either lysimeteric measurements or a local evaporation pan. This paper will examine the performance of ET models versus ET measured using lysimetery or pan evaporation and the performance of ET models when compared to a standard ETo model. A review of the performance of pan evaporation to the standard ETo model will also be performed.
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Wei, Jianli, Shida Tian, and Xinghua Yao. "Variable Structure Control for Hypersonic Vehicle Based on Model Reference." International Journal of Applied Physics and Mathematics 5, no. 2 (2015): 144–52. http://dx.doi.org/10.17706/ijapm.2015.5.2.144-152.

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Olla, Phillip, and Joseph Tan. "The M-Health Reference Model." International Journal of Healthcare Information Systems and Informatics 1, no. 2 (April 2006): 1–19. http://dx.doi.org/10.4018/jhisi.2006040101.

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Layne, Jeffery R., and Kevin M. Passino. "Fuzzy Model Reference Learning Control." Journal of Intelligent and Fuzzy Systems 4, no. 1 (1996): 33–47. http://dx.doi.org/10.3233/ifs-1996-4103.

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Dissertations / Theses on the topic "Model reference"

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Maeland, Jahn Andreas. "Model-reference neural control." Thesis, University of Salford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238757.

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Keller, Uwe E. "Qualitative model reference adaptive control." Thesis, Heriot-Watt University, 1999. http://hdl.handle.net/10399/592.

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Layne, Jeffery Ray. "Fuzzy model reference learning control." Connect to resource, 1992. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1159541293.

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Prasse, Michael John. "A model of anaphoric reference /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487325740719477.

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Moreno, Cavidad Julian. "Reference model for adaptive and intelligent educational systems supported by learning objects." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/70222.

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A aprendizagem assistida por computador, conhecida mais amplamente com o nome genérico de e-learning, converteu-se numa poderosa ferramenta com amplas potencialidades dentro do campo educativo. Mesmo assim, uma das maiores críticas que esta recebe é que na maioria dos casos os cursos que são implementados seguem um enfoque “one size fits all”, isto é, que todos os alunos recebem exatamente o mesmo conteúdo e da mesma maneira desconhecendo suas necessidades particulares. Esta falha radica não só na falta de interação direita entre aluno e tutor, senão também na falta de um desenho instrucional apropriado que considere alguns dos diversos enfoques disponíveis hoje em dia. Existem diversos enfoques que procuram solucionar este problema e adaptar o processo de ensino os estudantes. Pode-se dizer que na vanguarda de estes enfoques encontram-se os Sistemas Educacionais Inteligentes Adaptativos, os quais combinam as funcionalidades de dois enfoques: os Sistemas Hipermídia Educacionais Adaptativos y os Sistemas Tutoriais Inteligentes. Embora, logo de uma extensa revisão bibliográfica, se encontrou que existe ainda um inconveniente importante com este tipo de sistemas e em particular com seus modelos de referência: ou são demasiado simples, incluindo somente umas poucas funcionalidades; ou são demasiado complexos, o que dificulta seu desenho e implementação. Considerando este panorama, o objetivo principal de esta tese foi a definição de um modelo de referência intentando alcançar esse equilíbrio esquivo, de tal maneira que permita o desenho de cursos que se adaptem de una maneira efetiva e inteligente ao progresso e características de cada estudante, mas sem ser demasiado complexo. Outra propriedade importante desse modelo és que integra o uso de Objetos de Aprendizagem, promovendo assim a flexibilidade e a usabilidade. Para alcançar este objetivo geral, três sub modelos foram considerados: um modelo do domínio, um modelo do estudante y um modelo do tutor. O primeiro serve para estruturar o domínio de conhecimento e foi definido usando a noção de objetivo de aprendizagem junto com um esquema flexível multi-nível com operações opcionais de pré-requisitos. O segundo visa caracterizar aos estudantes e considera informação pessoal, de conhecimento e psico-cognitiva. O terceiro pode ser considerado como o coração do sistema e define as funcionalidades adaptativas consideradas: sequenciamento y navegação, apresentação de conteúdo, evacuação, y suporte colaborativo. Com o fim de clarificar os três sub modelos, assim como todos seus componentes e relações, se presentou um exemplo de instanciação que se denominou Doctus, o qual consiste em una ferramenta de autor para cursos adaptativos. Doctus não somente serviu para exemplificar o uso do modelo de referência em sua totalidade, mas também para refinar os sub modelos e alguns procedimentos involucrados. Como parte final de esta tese, se realizou também a implementação e validação preliminar de Doctus. Isto foi feito com 51 sujeitos, professores em diversos níveis de formação. Os resultados obtidos em esta etapa foram sobressalientes no sentido que todas as funcionalidades adaptativas foram bem avaliadas e todos os pesquisados manifestaram seu entusiasmo por contar com uma ferramenta que lhes ajudara em seus práticas docentes considerando a seus estudantes como indivíduos particulares.
Computer Aided Learning, known more widely with the generic name of e-learning, has become a powerful tool with lots of potentialities within educational field. Even though, one of the main critics that it receives is that in most cases the implemented courses follows a “one size fits all” approach, which means that all students receive the same content in the same way being unaware of their particular needs. This problem is not due only to the absence of direct interaction between student and tutor, but also because of the lack of an appropriate instructional design. There are several approaches which deal with this issue and look for adapt the teaching process to students. One could say that in the top of those approaches the Adaptive and Intelligent Educational Systems are situated, which merges the functionalities of two approaches: the Adaptive Educational Hypermedia Systems and the Intelligent Tutoring Systems. Nevertheless, after an extensive literature review, a major inconvenience is still found for this kind of systems and particularly for their reference models: or they are too simple, including just a few functionalities; or they are too complex, which difficult their design and implementation. Considering this panorama, the main objective of this dissertation thesis was the definition of a reference model trying to reach such an elusive equilibrium, in such a way that allows the design of courses which adapt themselves in an intelligent and effective way to the progress and characteristics of each student but without being too complex. Another important feature is that this model integrates Learning Objects, promoting this way flexibility and reusability. In order to achieve this general objective, three sub-models were considered: a domain model, a student model and a tutor model. The first one serves to structure the knowledge domain and was defined using the notion of learning goal and a flexible multilevel schema with optional prerequisite operations. The second one aids to characterize students and considered personal, knowledge and psycho-cognitive information. The third one may be considered as the hearth of the system and defines the adopted adaptive functionalities: sequencing and navigation, content presentation, assessment, and collaborative support. With the aim of clarify the three sub-models, as well as all their components and relationships, an instantiation example was also presented. Such an instantiation was called Doctus, an authoring tool for adaptive courses. Doctus was not only helpful to exemplify the setup of the referece model as a whole, but also to refine sub-models and several procedures envolved. As final part of the dissertation, the implementation and preliminary validation of Doctus was performed. This was done with 51 subjects, teachers from different formation levels. The obtained results in this stage were outstanding, all the adaptive functionalities were well evaluated and all of those polled felt enthusiastic about counting with a tool for helping them in their teaching practices considering students as particular individuals.
El aprendizaje asistido por computador, conocido más ampliamente con el nombre genérico de e-learning, se ha convertido en una poderosa herramienta con amplias potencialidades dentro del campo educativo. Aun así, una de las mayores críticas que este recibe es que en la mayoría de los casos los cursos que son implementados siguen un enfoque “one size fits all”, es decir, que todos los alumnos reciben exactamente el mismo contenido y de la misma manera desconociendo sus necesidades particulares. Esta falla radica no sólo en la falta de interacción directa entre alumno y tutor, sino también en la falta de un diseño instruccional apropiado que considere diversos de los enfoques disponibles hoy en día. Existen diversos enfoques que buscan solucionar este problema y adaptar el proceso de enseñanza a los estudiantes. Se podría decir que a la vanguardia de estos enfoques se encuentran los Sistemas Educacionales Inteligentes Adaptativos, los cuales combinan las funcionalidades de dos enfoques: los Sistemas Hipermedia Educacionales Adaptativos y los Sistemas Tutoriales Inteligentes. Sin embargo, luego de una extensa revisión bibliográfica, se encontró que existe aún un inconveniente importante con este tipo de sistemas y en particular con sus modelos de referencia: o son demasiado simples, incluyendo solamente unas pocas funcionalidades; o son demasiado complejos, lo cual dificulta su diseño e implementación. Considerando este panorama, el objetivo principal de esta tesis fue la definición de un modelo de referencia intentando alcanzar tal equilibrio esquivo, de tal manera que permita el diseño de cursos que se adapten de una manera efectiva e inteligente al progreso y características de cada estudiante pero sin ser demasiado complejo. Otra propiedad importante de dicho modelo es que integra el uso de Objetos de Aprendizaje, promoviendo así la flexibilidad y la reusabilidad. Con el fin de alcanzar este objetivo general, tres sub modelos fueron considerados: un modelo del dominio, un modelo del estudiante y un modelo del tutor. El primero sirve para estructurar el dominio de conocimiento y fue definido empleando la noción de objetivo de aprendizaje junto con un esquema flexible multinivel con operaciones opcionales de prerrequisitos. El segundo busca caracterizar los estudiantes y considera información personal, de conocimiento y psico-cognitiva. El tercero puede ser considerado como el corazón del sistema y define las funcionalidades adaptativas consideradas: secuenciamiento y navegación, presentación de contenido, evaluación, y soporte colaborativo. Con el fin de clarificar los tres sub modelos, así como todos sus componentes y relaciones, se presentó además un ejemplo de instanciación. Tal instanciación se denominó Doctus, el cual consiste en una herramienta de autor para cursos adaptativos. Doctus no solamente sirvió para ejemplificar el uso del modelo de referencia en su totalidad, sino también para refinar los sub modelos y algunos procedimientos involucrados. Como parte final de esta tesis, se realizó también la implementación y validación preliminar de Doctus. Esto se hizo con 51 sujetos, todos profesores en diversos niveles de formación. Los resultados obtenidos en esta etapa fueron sobresalientes en el sentido que todas las funcionalidades adaptativas fueron bien evaluadas y todos los encuestados manifestaron su entusiasmo por contar con una herramienta que les ayudara en sus prácticas docentes considerando a sus estudiantes como individuos particulares.
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Kergus, Pauline. "Data-driven model reference control in the frequency-domain : From model reference selection to controller validation." Thesis, Toulouse, ISAE, 2019. http://www.theses.fr/2019ESAE0031.

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Dans de nombreuses applications, aucun modèle physique du système n'est disponible, il s'agit alors de contrôler le système à partir de mesures entrées-sorties. Deux types d'approches sont envisageables : identifier un modèle du système puis l'utiliser afin de synthétiser un contrôleur, ce sont les méthodes indirectes, ou identifier le contrôleur directement à partir des données du système, ce sont les méthodes directes. Cette thèse se concentre sur les méthodes directes : l'objectif du travail présenté est de mettre en place une nouvelle méthode directe basée sur des données fréquentielles du système à contrôler. Après un tour d’horizon des méthodes indirectes existantes la méthode proposée est introduite. Il s’agit de résoudre un problème de suivi de modèle de référence : le problème d’identification est déporté du système vers le contrôleur. Dans ce cadre, deux techniques d’identification sont considérées dans cette thèse : l’interpolation de Loewner et l’approche des sous-espaces. De plus, les instabilités du système sont estimées en projetant les données fréquentielles disponibles. Cela permet de connaître les limites en performances du système et, par conséquent, de choisir des spécifications atteignables. Enfin, une analyse de la stabilité en boucle fermée permet d’obtenir un contrôleur stabilisant d’ordre réduit. Tout au long de ce travail, les différentes étapes de la méthode sont appliquées progressivement sur des exemples numériques. Pour finir, la méthode proposée est appliquée sur deux systèmes irrationnels, décrits par des équations aux dérivées partielles: un cristalliseur continu et un canal de génération. Ces deux exemples sont représentatifs de la catégorie de systèmes pour lesquels utiliser une méthode de contrôle directe est plus pertinent
In many applications, no physical description of the plant is available and the control law has to be designed on the basis of input-output measurements only. Two control strategies can then be considered : one can either identify a model of the plant and then use any kind of model-based technique (indirect methods) to obtain a control law, or use a data-driven strategy that directly compute the controller from the experimental data (direct methods). This work focuses on data-driven techniques : the objective of this thesis is to propose a new data-driven control technique based on frequency-domain data collected from the system to be controlled. After recalling some basics in feedback control, an overview of data-driven control is given. Then, the proposed method is introduced. It is a model reference technique : the identification problem is moved from the plant to the controller. In this work, two identification techniques are used to that purpose: the Loewner framework and the subspace approach. In addition, a technique is proposed to estimate the system’s instabilities. It allows to determine the performance limitations and to select achievable specifications. Finally, a stability condition, already known in data-driven control, is used during the reduction of the controller to ensure closed-loop stability. Along this thesis, the different steps of the method are progressively applied on two numercial examples. In the end, the proposed technique is applied on two irrational systems described by partial differential equations : a continuous crystallizer and an open-channel for hydroelectricity generation. These two examples illustrate the type of applications for which using a data-driven control method is indicated
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Zhang, Guoming. "Model reference control for nonlinear plants." Thesis, University of Manchester, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314208.

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Camara, C. D. J. "Plant identification using model reference techniques." Thesis, University of Cape Town, 1987. http://hdl.handle.net/11427/23544.

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Adesta, Erry Yulian Triblas. "A reference model for extended enterprise." Thesis, University of Huddersfield, 2002. http://eprints.hud.ac.uk/id/eprint/6714/.

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In today's highly competitive, volatile and increasingly global manufacturing environment, manufacturing companies are increasingly aware of the need for agility and effectiveness at the supply-chain level, rather than simply at company level. Business Process Re-engineering and the resulting emphasis on core competence has influenced a move towards de-centralisation, flatter organisation structures and increased use of "outsourcing". It has been said that it is now supply-chain versus supply-chain and that this poses both opportunity and threat for SMEs. While some work has been done in relation to developing the concept of integrated supply-chains, relatively little has been published with respect to the concept of "Extended Enterprise (EE)", the "highest' 'level of inter-enterprise integration. This thesis provides a thorough review of literature with respect to supply-chain integration and Extended Enterprise. Current practice is evaluated on the basis of the literature review and an analysis of a questionnaire and some Case Study companies. A detailed description of Extended Enterprise is provided and a conceptual reference model is developed, with the aim of providing a strategic planning tool, which will help organisations to identify the extent to which they operate as part of an EE. The model is intended also to help organisations in their evolution towards more effective operation within EE. One of the key characteristics/enablers of EE is stated as the existence of an organisational structure, which supports the effective identification, rationalisation and deployment of core competence within an EE. An approach based upon the concept of a "Process Breakdown Structure" is introduced and is evaluated in the context of a Case Study Company.
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Taylor, Chris. "Reference Models for IT Service Provision." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16047/.

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The new age, the "Information Age" (Davenport and Prusak 1997) has increased society's and businesses' reliance on Information Technology (IT). Hence, there is an increasing focus on the management of IT, not only from a technological perspective but also from a business perspective. This research, sponsored by REALTECH and the Australian Research Council, applies one of the modern management approaches, business process management (Hammer 1990), to the domain IT service provision, by designing a business process reference model for IT Service Provision. A reference model is an abstracted depiction of reality that serves as a standardised or suggestive conceptual basis for the design of enterprise specific models, usually within a like domain. They are one method of improving the efficiency and effectiveness of enterprise modelling and can also be used to standardise communication or capture knowledge. There is a general lack of theory regarding the classification, design and quality of reference models. The first part of this thesis attempts to fill these gaps, by presenting a reference model classification scheme, outlining 7 philosophies for the design of reference models and detailing 2 case studies on the user-perceived quality of business process reference models. Reference models and the Business Process Management Lifecycle (Rosemann 2000) are integrated to show how reference models can be applied to improve the efficiency and effectiveness of business process improvement projects. This reference model theory was then applied to produce a model for domain of IT Service Provision. Investment in IT has increased to become the largest single element of capital expenditure (Thorp 1998). Gartner predicted that organisations will spend over 10% of revenue on IT by 2005 (Haines 2000). A major input for this model is the ITIL best practice documents (CCTA 2000). The reference model focuses on Incident Management and used focus groups with participants from several large IT service providers to validate the models. The designed reference model is then tested in two case studies to determine its accuracy and usefulness. The thesis finishes with a discussion of the designed model, the effectiveness of the procedural model and provides suggestions for the design of other reference models. The final chapter provides a summary and an outlook for further research into the area.
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Books on the topic "Model reference"

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United States. Patent and Trademark Office. Technical reference model. 4th ed. Washington, D.C: Chief Information Officer, Office of System Architecture and Engineering, 1998.

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United States. Patent and Trademark Office. Technical reference model. 3rd ed. Washington, D.C: Chief Information Officer, Office of System Architecture and Engineering, 1997.

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Maeland, Jahn Andreas. Model-reference neural control. Salford: University of Salford, 1994.

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Carter, Clive S. Model drawings reference book. Shepperton: Ian Allan, 1985.

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Nguyen, Nhan T. Model-Reference Adaptive Control. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-56393-0.

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OSI reference model for telecommunications. New York: McGraw-Hill, 2002.

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Model reference adaptive control of manipulators. Taunton, Somerset, England: Research Studies Press, 1990.

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DAO object model: The definitive reference. Sebastopol, CA: O'Reilly, 2000.

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Etsuo, Yamamura. Introduction to model reference adaptive theory. Sapporo, Japan: Institute of Environmental Creation, 1993.

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Manufacturing planning and control: A reference model. Amsterdam: Elsevier, 1990.

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Book chapters on the topic "Model reference"

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Weik, Martin H. "reference model." In Computer Science and Communications Dictionary, 1443. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_15806.

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Ince, A. Nejat, Cem Evrendilek, Dag Wilhelmsen, and Fadıl Gezer. "Reference Model." In Planning and Architectural Design of Modern Command Control Communications and Information Systems, 65–71. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6159-0_4.

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Mauergauz, Yuri. "Reference Model." In Advanced Planning and Scheduling in Manufacturing and Supply Chains, 3–42. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27523-9_1.

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Smoryński, C. "Modal Model Theory." In Self-Reference and Modal Logic, 87–132. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4613-8601-8_3.

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Derakhshanmanesh, Mahdi. "Reference Implementation." In Model-Integrating Software Components, 189–237. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-09646-5_5.

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van den Heuve, W. J., and M. Jeusfeld. "Model Transformations with Reference Models." In Enterprise Interoperability II, 63–75. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-858-6_6.

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Wasano, Tetsuo, Yoshizumi Kobayashi, and Ken Sakamura. "CTRON Reference Model." In TRON Project 1988, 145–55. Tokyo: Springer Japan, 1988. http://dx.doi.org/10.1007/978-4-431-68081-9_11.

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Shekhar, Shashi, and Hui Xiong. "Linear Reference Model." In Encyclopedia of GIS, 612. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_695.

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Zeidler, Christian. "Reference model evaluation." In Mobile Support in Customer Loyalty Management, 197–219. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8301-5_6.

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Mans, Ronny S., Wil M. P. van der Aalst, and Rob J. B. Vanwersch. "Healthcare Reference Model." In Process Mining in Healthcare, 27–51. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16071-9_4.

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Conference papers on the topic "Model reference"

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"The Reference Model Models Clinicaltrials.Gov." In 2017 Summer Simulation Multi-Conference. Society for Modeling and Simulation International (SCS), 2017. http://dx.doi.org/10.22360/summersim.2017.scsc.022.

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Kannan, Suresh K., and Eric N. Johnson. "Model reference adaptive control with a constrained linear reference model." In 2010 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010. http://dx.doi.org/10.1109/cdc.2010.5717275.

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Nakagawa, Elisa Yumi, Flavio Oquendo, and Martin Becker. "RAModel: A Reference Model for Reference Architectures." In 2012 Joint Working IEEE/IFIP Conference on Software Architecture (WICSA) & European Conference on Software Architecture (ECSA). IEEE, 2012. http://dx.doi.org/10.1109/wicsa-ecsa.212.49.

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Schöne, René, Johannes Mey, Sebastian Ebert, and Uwe Aßmann. "Connecting conceptual models using relational reference attribute grammars." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3421437.

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Tahmasebi, Sanaz, Mojtaba Ahmadieh Khanesar, and Mohammad Teshnehlab. "Fuzzy reference model for adaptive indirect Takagi-Sugeno model reference control." In 2016 IEEE 13th International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2016. http://dx.doi.org/10.1109/icnsc.2016.7479009.

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Rost, Wolf. "Mining of DSLs and generator templates from reference applications." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3419492.

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Lau, Simon Boung-Yew, and Chien-Sing Lee. "Context aware reference model." In the 4th international conference on mobile technology, applications, and systems and the 1st international symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1378063.1378168.

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Bajorek, S., G. Hu, J. Ortensi, R. Hu, and J. Kelly. "BlueCRAB Microreactor Reference Model." In 2020 ANS Virtual Winter Meeting. AMNS, 2020. http://dx.doi.org/10.13182/t123-33025.

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Ertugrul, Taner, Mehmet Arif Adli, and Metin U. Salamci. "Model reference adaptive control design for helicopters using gain scheduled reference models." In 2016 17th International Carpathian Control Conference (ICCC). IEEE, 2016. http://dx.doi.org/10.1109/carpathiancc.2016.7501090.

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Bierling, Thomas, Maximilian Mühlegg, Florian Holzapfel, and Rudolf Maier. "Reference Model Modification for Robust Performance Conservation of Model Reference Adaptive Controllers." In AIAA Guidance, Navigation, and Control (GNC) Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2013. http://dx.doi.org/10.2514/6.2013-4512.

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Reports on the topic "Model reference"

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Neary, Vincent S. Reference Inflow Characterization for River Resource Reference Model (RM2). Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1034378.

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Gilman, P. SAM Photovoltaic Model Technical Reference. Office of Scientific and Technical Information (OSTI), May 2015. http://dx.doi.org/10.2172/1215213.

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Zhang, Qin Fen, Brennan T. Smith, and Wei Zhang. Small Hydro Reference Model Project. Office of Scientific and Technical Information (OSTI), October 2012. http://dx.doi.org/10.2172/1055120.

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Burns, Thomas, Elizabeth Fong, David Jefferson, Richard Knox, Leo Mark, Christopher Ready, Louis Reich, Nick Roussopoulos, and Walter Truszkowski. Reference model for DBMS standardization :. Gaithersburg, MD: National Bureau of Standards, 1985. http://dx.doi.org/10.6028/nbs.ir.85-3173.

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Barhak, Jacob. Supplemental Information: The Reference Model is a Multi-Scale Ensemble Model of COVID-19. Outbreak, May 2021. http://dx.doi.org/10.34235/b7eaa32b-1a6b-444f-9848-76f83f5a733c.

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Abstract:
The COVID-19 pandemic has accelerated research worldwide and resulted in a large number of computational models and initiatives. Models were mostly aimed at forecast and resulted in different predictions partially since models were based on different assumptions. In fact the idea that a computational model is just an assumption attempting to explain a phenomenon has not been sufficiently explored. Moreover, the ability to combine models has not been fully realized. The Reference Model for disease progression was performing this task for years for diabetes models and recently started modeling COVID-19. The Reference Model is an ensemble of models that is optimized to fit observed disease phenomenon. The ensemble has the ability to include model components from different sources that compete and cooperate. The recent advance in this model is the ability to include models calculated in different scales, making the model the first known multi-scale ensemble model. This manuscript will review these capabilities and show how multiple models can improve our ability to comprehend the COVID-19 pandemic.
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Fong, Elizabeth N., John Gersting, Kate Kinsley, Nancy McDonald, John North, Mark Sastry, and Edward Stull. Reference model for DBMS user facility. Gaithersburg, MD: National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nbs.ir.88-3709.

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Carpenter, B., T. Eckert, L. Ciavaglia, and J. Nobre. A Reference Model for Autonomic Networking. Edited by M. Behringer. RFC Editor, May 2021. http://dx.doi.org/10.17487/rfc8993.

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Barone, Matthew F., Jonathan Charles Berg, and Daniel Griffith. Reference Model 2: "Rev 0" Rotor Design. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1126471.

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Gilman, Paul, Nicholas A. DiOrio, Janine M. Freeman, Steven Janzou, Aron Dobos, and David Ryberg. SAM Photovoltaic Model Technical Reference 2016 Update. Office of Scientific and Technical Information (OSTI), March 2018. http://dx.doi.org/10.2172/1429291.

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Krause, James, and Gunter Stein. Structural Limitations of Model Reference Adaptive Controllers. Fort Belvoir, VA: Defense Technical Information Center, April 1989. http://dx.doi.org/10.21236/ada206759.

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