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Thematische Bibliographien / Objective data

Inhaltsverzeichnis

Zeitschriftenartikel
Dissertationen
Bücher
Buchteile
Konferenzberichte
Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Objective data“

Autor: Grafiati

Veröffentlicht am 29. Juni 2021

Zuletzt aktualisiert am 1. Februar 2022

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Zeitschriftenartikel zum Thema "Objective data"

1

Stix, Gary. "Objective Data." Scientific American 266, no. 3 (1992): 108. http://dx.doi.org/10.1038/scientificamerican0392-108.

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Carr, Edward L. "Objective Data Analysis Conference." Bulletin of the American Meteorological Society 68, no. 5 (1987): 481–85. http://dx.doi.org/10.1175/1520-0477-68.5.481.

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The Air Force Global Weather Central (AFGWC) hosted a conference on objective data analysis 2–4 October 1985. This was a continuation in a series of conferences on data analysis. Participants included both operational meteorologists and research meteorologists from various government's numerical weather prediction (NWP) facilities. The conference consisted of each participating facility reviewing their current status and future plans. Individual topics were then presented concerning data analysis, followed by small group discussions on meteorological and computational aspects of objective data

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Trapp, R. Jeffrey, and Charles A. Doswell. "Radar Data Objective Analysis." Journal of Atmospheric and Oceanic Technology 17, no. 2 (2000): 105–20. http://dx.doi.org/10.1175/1520-0426(2000)017<0105:rdoa>2.0.co;2.

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Gray, P. W., T. D. Mac Mahon, and M. U. Rajput. "Objective data evaluation procedures." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 286, no. 3 (1990): 569–75. http://dx.doi.org/10.1016/0168-9002(90)90918-v.

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K. Holland, Erin, and Major Major L. King. "Sleep Studies Need Objective Data." Journal of Psychosocial Nursing and Mental Health Services 46, no. 2 (2008): 13–14. http://dx.doi.org/10.3928/02793695-20080201-07.

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Smith, G. D., and Y. Ben-Shlomo. "Objective data trials are needed." BMJ 312, no. 7044 (1996): 1479–80. http://dx.doi.org/10.1136/bmj.312.7044.1479c.

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OBAYASHI, Shigeru. "Multi-Objective Optimization and Data Mining." Journal of the Society of Mechanical Engineers 109, no. 1050 (2006): 383–85. http://dx.doi.org/10.1299/jsmemag.109.1050_383.

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M’lan, Cyr Emile, and Ming-Hui Chen. "Objective Bayesian Inference for Bilateral Data." Bayesian Analysis 10, no. 1 (2015): 139–70. http://dx.doi.org/10.1214/14-ba890.

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Huber, Jessica E., Elaine Stathopoulos, Joan Sussman, and Kris Tjaden. "Obtaining Objective Data in Clinical Settings." ASHA Leader 15, no. 12 (2010): 12–15. http://dx.doi.org/10.1044/leader.ftr2.15122010.12.

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Noguchi, Kazutaka. "The objective lens for holographic data storage." Review of Laser Engineering 36, Supplement (2008): S27—S28. http://dx.doi.org/10.2184/lsj.36.s27.

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Dissertationen zum Thema "Objective data"

1

Kwoh, Chee Keong. "Probabilistic reasoning from correlated objective data." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307686.

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Kirkland, Oliver. "Multi-objective evolutionary algorithms for data clustering." Thesis, University of East Anglia, 2014. https://ueaeprints.uea.ac.uk/51331/.

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In this work we investigate the use of Multi-Objective metaheuristics for the data-mining task of clustering. We �first investigate methods of evaluating the quality of clustering solutions, we then propose a new Multi-Objective clustering algorithm driven by multiple measures of cluster quality and then perform investigations into the performance of different Multi-Objective clustering algorithms. In the context of clustering, a robust measure for evaluating clustering solutions is an important component of an algorithm. These Cluster Quality Measures (CQMs) should rely solely on the structur

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Fieldsend, Jonathan E. "Novel algorithms for multi-objective search and their application in multi-objective evolutionary neural network training." Thesis, University of Exeter, 2003. http://hdl.handle.net/10871/11706.

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Brown, Nathan C. (Nathan Collin). "Early building design using multi-objective data approaches." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123573.

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Thesis: Ph. D. in Architecture: Building Technology, Massachusetts Institute of Technology, Department of Architecture, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 201-219).<br>During the design process in architecture, building performance and human experience are increasingly understood through computation. Within this context, this dissertation considers how data science and interactive optimization techniques can be combined to make simulation a more effective component of a natural early design process. It focuses on conceptual design, since

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Mostaghim, Sanaz. "Multi-objective evolutionary algorithms data structures, convergence, and diversity /." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=974405604.

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Furst, Séverine. "Multi-objective optimization for joint inversion of geodetic data." Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTS017/document.

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La surface terrestre est affectée par de nombreux processus locaux tels que des événements volcaniques, des glissements de terrain ou des tremblements de terre. Parallèlement à ces processus naturels, les activités anthropiques, y compris l’extraction et le stockage des ressources profondes (par exemple, les minéraux ou les hydrocarbures) façonnent la Terre à différentes échelles spatiales et temporelles. Ces mécanismes produisent une déformation du sol qui peut être détectée par divers instruments et techniques géodésiques tel que le GNSS, l’InSAR, les inclinomètres. Le but de cette thèse est

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Ray, Subhasis. "Multi-objective optimization of an interior permanent magnet motor." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=116021.

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In recent years, due to growing environmental awareness regarding global warming, green cars, such as hybrid electric vehicles, have gained a lot of importance. With the decreasing cost of rare earth magnets, brushless permanent magnet motors, such as the Interior Permanent Magnet Motor, have found usage as part of the traction drive system in these types of vehicles. As a design issue, building a motor with a performance curve that suits both city and highway driving has been treated in this thesis as a multi-objective problem; matching specific points of the torque-speed curve to the desired

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Habib, Irfan. "Multi-objective optimisation of compute and data intensive e-science workflows." Thesis, University of the West of England, Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573383.

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Abstract Raw e-Science data, which may be, for example, MRI brain scans, data from a high energy physics detector or metric data from the earth observation projects needs to undergo a series of computations before meaningful knowledge can be derived. One way to. de- scribe these series of computations on raw e-Science data are workflows. Workflows have emerged as the principle mechanism for describing and enacting complex e-Science analy- sis on distributed infrastructures such as Grids. Workflows provide domain scientists with a systematic, repeatable and reproducible means of conducting scie

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Mostaghim, Sanaz [Verfasser]. "Multi-Objective Evolutionary Algorithms : Data Structures, Convergence, and Diversity / Sanaz Mostaghim." Aachen : Shaker, 2005. http://d-nb.info/1181620465/34.

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Ludick, Chantel Judith. "Disaggregating employment data to building level : a multi-objective optimisation approach." Diss., University of Pretoria, 2020. http://hdl.handle.net/2263/75596.

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The land use policies and development plans that are implemented in a city contribute to whether the city will be sustainable in the future. Therefore, when these policies are being established they should consider the potential impact on development. An analytical tool, such as land use change models, allow decision-makers to see the possible impact that these policies could have on development. Land use change models like UrbanSim make use of the relationship between households, buildings, and employment opportunities to model the decisions that people make on where to live and work. To be a

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Bücher zum Thema "Objective data"

1

Coello, Carlos A. Coello. Swarm intelligence for multi-objective problems in data mining. Springer Verlag, 2009.

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Coello, Carlos Artemio Coello, Satchidananda Dehuri, and Susmita Ghosh, eds. Swarm Intelligence for Multi-objective Problems in Data Mining. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03625-5.

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A, Hillison William, ed. Auditing & EDP: Objective questions and explanations. 5th ed. Gleim Publications, 1992.

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Lieberman, Elliot R. Multi-objective programming in the USSR. Academic Press, 1991.

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Gleim, Irvin N. Auditing & EDP: Objective questions and explanations. 4th ed. Gleim Publications, 1991.

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Gleim, Irvin N. Auditing & EDP: Objective questions and explanations. 2nd ed. Accounting Publications, 1985.

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A, Hillison William, and Irwin Grady M, eds. Auditing & EDP: Objective questions and explanations. 3rd ed. Accounting Publications, 1988.

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Lieberman, Elliot R. Multi-objective programming in the USSR. Academic, 1991.

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Gleim, Irvin N. Auditing & systems: Objective questions and explanations. 7th ed. Gleim Publications, 1997.

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10

Franke, Richard H. Laplacian smoothing splines with generalized cross validation for objective analysis of meteorological data. Naval Postgraduate School, 1985.

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Buchteile zum Thema "Objective data"

1

Dovey, James, and Ash Furrow. "Data Management with Core Data." In Beginning Objective-C. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4369-4_8.

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Campbell, Matthew. "Core Data." In Objective-C Recipes. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4372-4_10.

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Lee, Keith. "Foundation Functions and Data Types." In Pro Objective-C. Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-5051-7_13.

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Bennett, Gary, Mitch Fisher, and Brad Lees. "Comparing Data." In Objective-C for Absolute Beginners. Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-2833-2_9.

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Bennett, Gary, Mitch Fisher, and Brad Lees. "Comparing Data." In Objective-C for Absolute Beginners. Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3654-2_9.

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Kaczmarek, Stefan, Brad Lees, Gary Bennett, and Mitch Fisher. "Comparing Data." In Objective-C for Absolute Beginners. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3429-7_9.

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Bennett, Gary, Brad Lees, and Mitchell Fisher. "Comparing Data." In Objective-C for Absolute Beginners. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1904-1_9.

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Dovey, James, and Ash Furrow. "Networking: Connections, Data, and the Cloud." In Beginning Objective-C. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4369-4_6.

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Mukhopadhyay, Anirban. "Incorporating Gene Ontology Information in Gene Expression Data Clustering Using Multiobjective Evolutionary Optimization: Application in Yeast Cell Cycle Data." In Multi-Objective Optimization. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1471-1_3.

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Mallik, Saurav, Tapas Bhadra, Soumita Seth, Sanghamitra Bandyopadhyay, and Jianjiao Chen. "Multi-Objective Optimization Approaches in Biological Learning System on Microarray Data." In Multi-Objective Optimization. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1471-1_7.

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Konferenzberichte zum Thema "Objective data"

1

Benouaret, Idir, Sihem Amer-Yahia, Christiane Kamdem-Kengne, and Jalil Chagraoui. "A Bi-Objective Approach for Product Recommendations." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006503.

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Itonaga, Makoto, Fumihiko Ito, and Toshiya Saito. "Analysis of chromatic aberration of single objective lens and correction of that of a NA=0.85 objective lens." In Optical Data Storage. OSA, 2003. http://dx.doi.org/10.1364/ods.2003.wa7.

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Burmester, G., and H. Rohler. "Objective-based Image Data Management." In Second EAGE Borehole Geology Workshop. EAGE Publications BV, 2017. http://dx.doi.org/10.3997/2214-4609.201702393.

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Attaoui, Mohammed Oualid, Hanene Azzag, Mustapha Lebbah, and Nabil Keskes. "Multi-objective data stream clustering." In GECCO '20: Genetic and Evolutionary Computation Conference. ACM, 2020. http://dx.doi.org/10.1145/3377929.3389930.

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Zheng, Yong, and David (Xuejun) Wang. "Multi-Objective Recommendations." In KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2021. http://dx.doi.org/10.1145/3447548.3470788.

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Jalali, Leila, Misbah Khan, and Rahul Biswas. "Learning and Multi-Objective Optimization for Automatic Identity Linkage." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622581.

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Pietri, Ilia, Yannis Chronis, and Yannis Ioannidis. "Multi-objective optimization of scheduling dataflows on heterogeneous cloud resources." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8257946.

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Zeng, Fanchao, James Decraene, Malcolm Yoke Hean Low, Cai Wentong, Philip Hingston, and Suiping Zhou. "High-dimensional objective-based data farming." In 2011 Ieee Symposium On Computational Intelligence For Security And Defence Applications - Part Of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/cisda.2011.5945942.

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Antony, Shyam, Ping Wu, Divyakant Agrawal, and Amr El Abbadi. "MOOLAP: Towards Multi-Objective OLAP." In 2008 IEEE 24th International Conference on Data Engineering (ICDE 2008). IEEE, 2008. http://dx.doi.org/10.1109/icde.2008.4497567.

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Shi, Chuan, Xiangnan Kong, Philip S. Yu, and Bai Wang. "Multi-Objective Multi-Label Classification." In Proceedings of the 2012 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611972825.31.

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Berichte der Organisationen zum Thema "Objective data"

1

Hunt, J. W. Tank safety screening data quality objective. Revision 1. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/61107.

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Gydesen, S. Status of document search and data quality objective efforts. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/10107852.

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Gydesen, S. Status of document search and data quality objective efforts. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/6992873.

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Irvine, Nelson. Analysis of the Objective Data From Fleet Battle Experiment Hotel. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada389211.

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Irvine, Nelson. Objective Data from Fleet Battle Experiment Foxtrot, Golf, and Hotel. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada389356.

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Gates, C. M., and M. R. Beckette. Identification of physical properties for the retrieval data quality objective process. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/86993.

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Tung, S. L. Users Guide for Normal Mode Objective Analysis of Global Data Assimilation,. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada160373.

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Meacham, J. E. Data quality objective to support resolution of the organic solvent safety issue. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/341237.

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Kirkbride, R. A. Technical work plan for the privatization waste characterization data quality objective process. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/341255.

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Mulkey, C. H. ,. Westinghouse Hanford. Data quality objective for regulatory requirements for dangerous waste sampling and analysis. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/659219.

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