Relevant bibliographies by topics / Ensemble

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Ensemble'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Ensemble"

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Lawrence, Andrew R., and James A. Hansen. "A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size." Monthly Weather Review 135, no. 4 (2007): 1424–38. http://dx.doi.org/10.1175/mwr3357.1.

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Abstract An ensemble-based data assimilation approach is used to transform old ensemble forecast perturbations with more recent observations for the purpose of inexpensively increasing ensemble size. The impact of the transformations are propagated forward in time over the ensemble’s forecast period without rerunning any models, and these transformed ensemble forecast perturbations can be combined with the most recent ensemble forecast to sensibly increase forecast ensemble sizes. Because the transform takes place in perturbation space, the transformed perturbations must be centered on the ens
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Rodríguez Molina, Javier. "Variantes léxicas y gramaticales del adverbio ensemble en la documentación medieval." Cuadernos del Instituto Historia de la Lengua, no. 7 (January 16, 2023): 405–24. http://dx.doi.org/10.58576/cilengua.vi7.129.

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En este artículo se estudia la evolución histórica del adverbiomedieval ensemble, que apenas si ha recibido atención en labibliografía. A partir de un exhaustivo análisis de documentos notariales,se defiende que ensemble no es un préstamo del francés antiguo,como sugieren varios estudios previos, sino un desarrollovernáculo del latín peninsular ĬN SĬMŬL. Esta hipótesis se basa tantoen la distribución geográfica de los datos medievales como en la variaciónmorfológica que presenta el adverbio (ensemble, ensembra,ensembla). En la Edad Media ensemble presenta un patrón de distribucióndialectal cla
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Fiskvik, Anne Margrete. "La Famille Dansant. Investigating the Family Structure and Repertory of the Johannesénske Balletselskab." Nordic Theatre Studies 27, no. 2 (2015): 104. http://dx.doi.org/10.7146/nts.v27i2.24254.

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The performance history of the Johannesénske Balletselskab spans a long period. In different shapes, sizes and names the ensemble was on the road for 30 years. This article analyses the activities of the Johannesénske enterprise through the lenses of itinerant performance traditions. Two features are discussed in this article: the reliance on family members as performers and the ensemble’s diverse repertory. The ensemble featured a repertory popular in its own time, consisting chiefly of national and character dances as well as pantomimes. Arguably, an investigation of the ensemble’s performan
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Liu, Li Min, and Xiao Ping Fan. "A Survey: Clustering Ensemble Selection." Advanced Materials Research 403-408 (November 2011): 2760–63. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2760.

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Traditional clustering ensemble combines all of the available clustering partitions to get the final clustering result. But in supervised classification area,it has been known that selective classifier ensembles can always achieve better solutions.Following the selective classifier ensembles,the question of clustering ensemble is defined as clustering ensemble selection.The paper introduces the concept of clustering ensemble selection and gives the survey of clustering ensemble selection algorithms.
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Opitz, D., and R. Maclin. "Popular Ensemble Methods: An Empirical Study." Journal of Artificial Intelligence Research 11 (August 1, 1999): 169–98. http://dx.doi.org/10.1613/jair.614.

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An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of the single classifiers in the ensemble. Bagging (Breiman, 1996c) and Boosting (Freund & Shapire, 1996; Shapire, 1990) are two relatively new but popular methods for producing ensembles. In this paper we evaluate these methods on 23 data sets using both neural networks and decision trees as our classification algorithm. Our results clearly
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Saqib, Malik, and Sharma Narendra. "A Vast Review of Recognizing the Presence of Android Malware Based on Ensemble Machine Learning Technique." Indian Journal of Science and Technology 17, no. 2 (2024): 149–65. https://doi.org/10.17485/IJST/v17i2.2406.

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Abstract <strong>Background:</strong>&nbsp;It is evaluated that there is 70% to 80% of smartphone users have an Android mobile. Given its trend, a lot of malware strikes on the Android OS. In 2018, the largest number of malware attacks was identified, when there were 10.5 billion such malicious activity detected worldwide. Machine learning has emerged as a promising approach for detecting Android malware, and Ensemble machine learning has been shown to enhance the accuracy of malware detection in other domains. Objectives: In this paper, the systematic literature review were conducted using na
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Kolczynski, Walter C., David R. Stauffer, Sue Ellen Haupt, Naomi S. Altman, and Aijun Deng. "Investigation of Ensemble Variance as a Measure of True Forecast Variance." Monthly Weather Review 139, no. 12 (2011): 3954–63. http://dx.doi.org/10.1175/mwr-d-10-05081.1.

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Abstract The uncertainty in meteorological predictions is of interest for applications ranging from economic to recreational to public safety. One common method to estimate uncertainty is by using meteorological ensembles. These ensembles provide an easily quantifiable measure of the uncertainty in the forecast in the form of the ensemble variance. However, ensemble variance may not accurately reflect the actual uncertainty, so any measure of uncertainty derived from the ensemble should be calibrated to provide a more reliable estimate of the actual uncertainty in the forecast. A previous stud
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Kioutsioukis, I., and S. Galmarini. "<i>De praeceptis ferendis</i>: good practice in multi-model ensembles." Atmospheric Chemistry and Physics 14, no. 21 (2014): 11791–815. http://dx.doi.org/10.5194/acp-14-11791-2014.

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Abstract. Ensembles of air quality models have been formally and empirically shown to outperform single models in many cases. Evidence suggests that ensemble error is reduced when the members form a diverse and accurate ensemble. Diversity and accuracy are hence two factors that should be taken care of while designing ensembles in order for them to provide better predictions. Theoretical aspects like the bias–variance–covariance decomposition and the accuracy–diversity decomposition are linked together and support the importance of creating ensemble that incorporates both these elements. Hence
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Alazba, Amal, and Hamoud Aljamaan. "Software Defect Prediction Using Stacking Generalization of Optimized Tree-Based Ensembles." Applied Sciences 12, no. 9 (2022): 4577. http://dx.doi.org/10.3390/app12094577.

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Software defect prediction refers to the automatic identification of defective parts of software through machine learning techniques. Ensemble learning has exhibited excellent prediction outcomes in comparison with individual classifiers. However, most of the previous work utilized ensemble models in the context of software defect prediction with the default hyperparameter values, which are considered suboptimal. In this paper, we investigate the applicability of a stacking ensemble built with fine-tuned tree-based ensembles for defect prediction. We used grid search to optimize the hyperparam
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LaRow, T. E., S. D. Cocke, and D. W. Shin. "Multiconvective Parameterizations as a Multimodel Proxy for Seasonal Climate Studies." Journal of Climate 18, no. 15 (2005): 2963–78. http://dx.doi.org/10.1175/jcli3448.1.

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Abstract A six-member multicoupled model ensemble is created by using six state-of-the-art deep atmospheric convective schemes. The six convective schemes are used inside a single model and make up the ensemble. This six-member ensemble is compared against a multianalysis ensemble, which is created by varying the initial start dates of the atmospheric component of the coupled model. Both ensembles were integrated for seven months (November–May) over a 12-yr period from 1987 to 1998. Examination of the sea surface temperature and precipitation show that while deterministic skill scores are slig
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Dissertations / Theses on the topic "Ensemble"

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Abbasian, Houman. "Inner Ensembles: Using Ensemble Methods in Learning Step." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31127.

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A pivotal moment in machine learning research was the creation of an important new research area, known as Ensemble Learning. In this work, we argue that ensembles are a very general concept, and though they have been widely used, they can be applied in more situations than they have been to date. Rather than using them only to combine the output of an algorithm, we can apply them to decisions made inside the algorithm itself, during the learning step. We call this approach Inner Ensembles. The motivation to develop Inner Ensembles was the opportunity to produce models with the similar advanta
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Wild, Florence. "ENSEMBLE PIECE." Thesis, Konstfack, Institutionen för Konst (K), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-5774.

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The essay Ensemble Piece contemplates the nature of how one observes, labours, and translates as active and passive movements, repeated, reconstructed. The text is a companion piece to the installations Silver Tea and Silver Tea Suite. The works discussed in this text make up the installation Silver Tea. A contemplation of forms that kaleidoscopically revolve around each other, whose imagery, methodologies and forms reflect and morph into one another, a looping, repetitious rhythm that is not, however, confined to a circuitous nature. Silver Tea rests in a space and timeframe between suggestio
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Yang, Shuang. "Multistage neural network ensemble : adaptive combination of ensemble results." Thesis, London Metropolitan University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425920.

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Anderson, Andrew E. (Andrew Edwin). "Hailstones and Birdcages for Wind Ensemble." Thesis, University of North Texas, 1990. https://digital.library.unt.edu/ark:/67531/metadc500256/.

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Hailstones and Birdcages is a composition of approximately thirteen minutes' duration and is scored for two flutes and piccolo, two oboes and english horn, three Eb clarinets, E clarinete, bass clarinet, two bassoons, two Eb alto saxophones, Bb tenor saxophone, three Bb trumpets, four F horns, three trombones, euphonium, two tubas, and three percussionists. Four instruments--one each of flute, oboe, Bb clarinet, and trombone--are used in concertante like fashion, and there are prominent solo passages for the first bassoon, as well. The work is a single movement in three sections, fast - slow -
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McDonald, Richard F. (Richard Frederic). "Kinetico for Chamber Wind Ensemble." Thesis, North Texas State University, 1985. https://digital.library.unt.edu/ark:/67531/metadc504015/.

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This single movement work is written for 2 flutes, 2 oboes, 3 clarinets in Bb, bass clarinet in Bb, 2 bassoons, alto saxophone in Eb, 2 horns in F, 2 trumpets in Bb, trombone, euphonium, tuba, contra bass, and 3 percussion. The approximate length is eight minutes. Both traditional and proportional systems of notation are employed. The entire piece is freely chromatic with some implications of whole tone and other nondiatonic scales. The harmonies are tertian yet have no functional tonal basis. Changing meters with asymmetrical divisions are used in all sections except C and E, which have time
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Cech, Andrew J. "Brother's lament for wind ensemble." Ohio : Ohio University, 2009. http://www.ohiolink.edu/etd/view.cgi?ohiou1244578892.

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Guérin, Laura. "Manger ensemble : mourir ensemble : ethnographie du repas collectif en Ehpad." Paris, EHESS, 2016. http://www.theses.fr/2016EHES0121.

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A partir d'une démarche ethnographique, cette thèse interroge le maintien du repas collectif en Établissement d'Hébergement pom Personnes Âgées Dépendantes (Ehpad). Préconisé par les politiques de santé publique et la littérature professionnelle comme gage de soin et de sociabilité, le repas en commun n'en est pas moins une épreuve quotidienne au sein des établissements, qui impose des ajustements pratiques afin de correspondre, autant que possible, aux attentes sociales qu'il cristallise. Parce qu'il exige chaque jour la mise en groupe des résidents, concentre la vie en collectivité, nous l'e
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Echevarría, García Joaquín, and Barrantes James José Ordinola. "Proyecto ensemble interactions." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2016. http://hdl.handle.net/10757/622175.

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En la actualidad, no existe gran variedad de herramientas que permitan a la comunidad de desarrolladores Android implementar aplicaciones orientadas a entornos de múltiples pantallas y que, adicionalmente, les permitan cumplir con lo descrito por Ensemble Interactions y los patrones de diseño definidos para estos entornos, los cuales, en conjunto, son conceptos que proponen el trabajo en conjunto de todos los dispositivos disponibles en un mismo entorno. Por otro lado, de las pocas herramientas que permiten el desarrollo de este tipo de aplicaciones, algunas han sido implementadas por grandes
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Alza, Guzmán Diego Andrés, and Martinez Jean Carlo Canales. "Ensemble interactions iOS." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2018. http://hdl.handle.net/10757/622927.

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Definir e implementar un SDK que integre las principales características definidas por Ensemble Interactions (EI). Para ello, se analizarán e implementarán los patrones descritos por E.I. De esta forma, la investigación brindará el marco teórico necesario para el correcto entendimiento de EI y los seis patrones principales que lo definen. La interpretación de los resultados obtenidos en el análisis de los patrones será fundamental debido a que esta será la base que respaldara los artefactos que se realizaran a lo largo del proyecto. Asimismo, la implementación se dividirá en entregables: Desa
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Andersson, Erik. "Kommunikation i ensemble." Thesis, Örebro universitet, Musikhögskolan, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-48327.

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Books on the topic "Ensemble"

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Cosier, Tony. Ensemble. Moonstone Press, 1985.

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Comeau, Raymond F. Ensemble. 6th ed. Holt, Rinehart and Winston, 1999.

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Comeau, Raymond F. Ensemble. 6th ed. Holt, Rinehart and Winston, 1999.

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Comeau, Raymond F. Ensemble. 6th ed. Holt, Rinehart and Winston, 1998.

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Comeau, Raymond F. Ensemble. 5th ed. Holt, Rinehart and Winston, 1994.

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Comeau, Raymond F. Ensemble. 5th ed. Holt, Rinehart and Winston, 1994.

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Comeau, Raymond F. Ensemble. 5th ed. Holt, Rinehart and Winston, 1994.

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Glass, Philip. Songs from liquid days. CBS, 1986.

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McDonald, Donna. The odyssey of the Philip Jones Brass Ensemble. Editions Bim, 1986.

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Brine, Patricia. Enigmatic ensemble. Macbee Pub., 2005.

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Book chapters on the topic "Ensemble"

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Zhou, Zhi-Hua. "Ensemble." In Encyclopedia of Database Systems. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_768-2.

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Zhou, Zhi-Hua. "Ensemble." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_768.

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Vens, Celine. "Ensemble." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_614.

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Zhou, Zhi-Hua. "Ensemble." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_768.

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Zhou, Zhi-Hua. "Ensemble Pruning." In Ensemble Methods, 2nd ed. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003587774-6.

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Zhou, Zhi-Hua. "Clustering Ensemble." In Ensemble Methods, 2nd ed. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003587774-7.

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Brazdil, Pavel, Jan N. van Rijn, Carlos Soares, and Joaquin Vanschoren. "Metalearning in Ensemble Methods." In Metalearning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-67024-5_10.

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AbstractThis chapter discusses some approaches that exploit metalearning methods in ensemble learning. It starts by presenting a set of issues, such as the ensemble method used, which affect the process of ensemble learning and the resulting ensemble. In this chapter we discuss various lines of research that were followed. Some approaches seek an ensemble-based solution for the whole dataset, others for individual instances. Regarding the first group, we focus on metalearning in the construction, pruning and integration phase. Modeling the interdependence of models plays an important part in t
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Resseguier, Valentin, Yicun Zhen, and Bertrand Chapron. "Constrained Random Diffeomorphisms for Data Assimilation." In Mathematics of Planet Earth. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40094-0_13.

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AbstractFor ensemble-based data assimilation purposes, there is a definite need for relevant ensemble sampling tools. Indeed, the quality and spreading of these ensembles have deep implications in the quality of the data assimilation, and—until recently—those so-called covariance inflation tools have mostly relied on unsuitable linear Gaussian frameworks. A promising alternative is the generation of ensembles through a stochastic remapping of the physical space.
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Zhou, Zhi-Hua. "Semi-Supervised Ensemble." In Ensemble Methods, 2nd ed. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003587774-9.

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Zhou, Zhi-Hua. "Introduction." In Ensemble Methods, 2nd ed. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003587774-1.

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Conference papers on the topic "Ensemble"

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Cheung, Catherine, and Zouhair Hamaimou. "Ensemble Integration Methods for Load Estimation." In Vertical Flight Society 78th Annual Forum & Technology Display. The Vertical Flight Society, 2022. http://dx.doi.org/10.4050/f-0078-2022-17553.

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Helicopter component load estimation can be achieved through a variety of machine learning techniques and algorithms. To increase confidence in the load estimation process, ensemble methods are employed combining multiple individual load estimators that increase predictive stability across flights and add robustness to noisy data. In this work, several load estimation methods are applied to a variety of machine learning algorithms to build a large library of individual load estimation models for main rotor yoke loads from 28 flight state and control system parameters. This paper explores sever
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Alabi, Oluwafemi S., Xunlei Wu, Jonathan M. Harter, et al. "Comparative visualization of ensembles using ensemble surface slicing." In IS&T/SPIE Electronic Imaging, edited by Pak Chung Wong, David L. Kao, Ming C. Hao, et al. SPIE, 2012. http://dx.doi.org/10.1117/12.908288.

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Yan, Leyi, Linda Wang, Sihang Liu, and Yi Ding. "EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting." In E-Energy '25: The 16th ACM International Conference on Future and Sustainable Energy Systems. ACM, 2025. https://doi.org/10.1145/3679240.3734630.

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Nemani, Venkat, Adam Thelen, Chao Hu, and Steve Daining. "Dynamically Weighted Ensemble of Diverse Learners for Remaining Useful Life Prediction." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-90252.

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Abstract A traditional ensemble approach to predicting the remaining useful life (RUL) of equipment and other assets has been constructing data-driven and model-based ensembles using identical estimators. This ensemble approach may perform well on quality data collected from a design-of-experiments test but may ultimately fail when deployed in the field because of higher-than-expected noise, missing measurements, and different degradation trends. In such work environments, the high similarity of the learners can lead to large under/overestimates of RUL, where the ensemble is only as accurate a
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Hislop, Gregory W., Lillian Cassel, Lois Delcambre, Edward Fox, Rick Furuta, and Peter Brusilovsky. "Ensemble." In the 10th ACM conference. ACM Press, 2009. http://dx.doi.org/10.1145/1631728.1631783.

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Lillian (Boots), Cassel, Hislop Gregory, and Bharath Nadella. "Ensemble." In the 14th annual ACM SIGCSE conference. ACM Press, 2009. http://dx.doi.org/10.1145/1562877.1562997.

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Cassel, Lillian, Lois Delcambre, and Gregory Hislop. "Ensemble." In the 45th ACM technical symposium. ACM Press, 2014. http://dx.doi.org/10.1145/2538862.2544252.

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Cadot, Sidney, Frits Kuijlman, Koen Langendoen, Kees van Reeuwijk, and Henk Sips. "ENSEMBLE." In the ACM SIGPLAN workshop. ACM Press, 2001. http://dx.doi.org/10.1145/384197.384207.

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Cadot, Sidney, Frits Kuijlman, Koen Langendoen, Kees van Reeuwijk, and Henk Sips. "ENSEMBLE." In the 2001 ACM SIGPLAN workshop. ACM Press, 2001. http://dx.doi.org/10.1145/384198.384207.

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Xiang, P. F., C. Williams, S. X. Yang, et al. "Ensemble." In the 2008 international workshop. ACM Press, 2008. http://dx.doi.org/10.1145/1454247.1454259.

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Reports on the topic "Ensemble"

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Cobb, Kelly. Saori Ensemble. Iowa State University, Digital Repository, 2015. http://dx.doi.org/10.31274/itaa_proceedings-180814-1253.

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Chae, May. Lucky Ensemble. Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1586.

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Wang, Xugueng. Ensemble Forecasting with the Ensemble Transform Kalman Filter. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada429161.

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Pulley, Zoe, and kristin caskey. Zero Waste Ensemble. Iowa State University, Digital Repository, 2015. http://dx.doi.org/10.31274/itaa_proceedings-180814-1202.

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Orzada, Belinda T. Denim and Silk Ensemble. Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-235.

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Pedersen, Gjertrud. Symphonies Reframed. Norges Musikkhøgskole, 2018. http://dx.doi.org/10.22501/nmh-ar.481294.

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Symphonies Reframed recreates symphonies as chamber music. The project aims to capture the features that are unique for chamber music, at the juncture between the “soloistic small” and the “orchestral large”. A new ensemble model, the “triharmonic ensemble” with 7-9 musicians, has been created to serve this purpose. By choosing this size range, we are looking to facilitate group interplay without the need of a conductor. We also want to facilitate a richness of sound colours by involving piano, strings and winds. The exact combination of instruments is chosen in accordance with the features of
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Buckley, R., S. Chiswell, R. Kurzeja, G. Maze, B. Viner, and D. Werth. Advanced Atmospheric Ensemble Modeling Techniques. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1395969.

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Orzada, Belinda T. Upcycle and Zero Waste Ensemble. Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-236.

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Szunyogh, Istvan. Tropical Cyclone Ensemble Data Assimilation. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada542060.

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Peil, Steven, Scott Crane, James Hanssen, Thomas B. Swanson, and Christopher B. Ekstrom. An Ensemble of Atomic Fountains. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada566333.

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