Literatura académica sobre el tema "Multidimensionnal network"
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Artículos de revistas sobre el tema "Multidimensionnal network"
Xuan, Qi, Xiaodi Ma, Chenbo Fu, Hui Dong, Guijun Zhang y Li Yu. "Heterogeneous multidimensional scaling for complex networks". International Journal of Modern Physics C 26, n.º 02 (febrero de 2015): 1550023. http://dx.doi.org/10.1142/s0129183115500230.
Texto completoAbrahão, Felipe S., Klaus Wehmuth, Hector Zenil y Artur Ziviani. "Algorithmic Information Distortions in Node-Aligned and Node-Unaligned Multidimensional Networks". Entropy 23, n.º 7 (29 de junio de 2021): 835. http://dx.doi.org/10.3390/e23070835.
Texto completoGarcez, Thalles V. y Przemyslaw Szufel. "Multidimensional Risk Management for Underground Electricity Networks". Studies in Logic, Grammar and Rhetoric 37, n.º 1 (8 de agosto de 2014): 51–69. http://dx.doi.org/10.2478/slgr-2014-0017.
Texto completoObrubov, M. y S. Kirillova. "USING LSTM NETWORK FOR SOLVING THE MULTIDIMENTIONAL TIME SERIES FORECASTING PROBLEM". National Association of Scientists 2, n.º 68 (1 de julio de 2021): 43–48. http://dx.doi.org/10.31618/nas.2413-5291.2021.2.68.450.
Texto completoVeiga, André, E. Glen Weyl y Alexander White. "Multidimensional Platform Design". American Economic Review 107, n.º 5 (1 de mayo de 2017): 191–95. http://dx.doi.org/10.1257/aer.p20171044.
Texto completoMANGAL, MANISH y MANU PRATAP SINGH. "ANALYSIS OF MULTIDIMENSIONAL XOR CLASSIFICATION PROBLEM WITH EVOLUTIONARY FEEDFORWARD NEURAL NETWORKS". International Journal on Artificial Intelligence Tools 16, n.º 01 (febrero de 2007): 111–20. http://dx.doi.org/10.1142/s0218213007003229.
Texto completoBLOCK, PER y THOMAS GRUND. "Multidimensional homophily in friendship networks". Network Science 2, n.º 2 (agosto de 2014): 189–212. http://dx.doi.org/10.1017/nws.2014.17.
Texto completoLi, Siming, Zhangxi Lin, Jiaxian Qiu, Roozmehr Safi y Zhongyi Xiao. "How friendship networks work in online P2P lending markets". Nankai Business Review International 6, n.º 1 (2 de marzo de 2015): 42–67. http://dx.doi.org/10.1108/nbri-01-2014-0010.
Texto completoPavan, Elena. "Embedding Digital Communications Within Collective Action Networks: A Multidimensional Network Approach". Mobilization: An International Quarterly 19, n.º 4 (1 de diciembre de 2014): 441–55. http://dx.doi.org/10.17813/maiq.19.4.w24rl524u074126k.
Texto completoDařena, František, Alexander Troussov y Jan Žižka. "Simulating activation propagation in social networks using the graph theory". Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 58, n.º 3 (2010): 21–28. http://dx.doi.org/10.11118/actaun201058030021.
Texto completoTesis sobre el tema "Multidimensionnal network"
Ben, Chaabene Nour El Houda. "Détection d'utilisateurs violents et de menaces dans les réseaux sociaux". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS001.
Texto completoOnline social networks are an integral part of people's daily social activity. They provide platforms to connect people from all over the world and share their interests. Recent statistics indicate that 56% of the world's population use these social media. However, these network services have also had many negative impacts and the existence of phenomena of aggression and intimidation in these spaces is inevitable and must therefore be addressed. Exploring the complex structure of social networks to detect violent behavior and threats is a challenge for data mining, machine learning, and artificial intelligence. In this thesis work, we aim to propose new approaches for the detection of violent behavior in social networks. Our approaches attempt to resolve this problem for several practical reasons. First, different people have different ways of expressing the same violent behavior. It is desirable to design an approach that works for everyone because of the variety of behaviors and the various ways in which they are expressed. Second, the approaches must have a way to detect potential unseen abnormal behaviors and automatically add them to the training set. Third, the multimodality and multidimensionality of the data available on social networking sites must be taken into account for the development of data mining solutions that will be able to extract relevant information useful for the detection of violent behavior. Finally, approaches must consider the time-varying nature of networks to process new users and links and automatically update built models. In the light of this and to achieve the aforementioned objectives, the main contributions of this thesis are as follows: - The first contribution proposes a model for detecting violent behavior on Twitter. This model supports the dynamic nature of the network and is capable of extracting and analyzing heterogeneous data. - The second contribution introduces an approach for detecting atypical behaviors on a multidimensional network. This approach is based on the exploration and analysis of the relationships between the individuals present on this multidimensional social structure. - The third contribution presents a framework for identifying abnormal people. This intelligent framework is based on the exploitation of a multidimensional model which takes as input multimodal data coming from several sources, capable of automatically enriching the learning set by the violent behaviors detected and considers the dynamicity of the data in order to detect new violent behaviors that appear on the network. This thesis describes achievements combining data mining techniques with new machine learning techniques. To prove the performance of our experimental results, we sums based on real data taken from three popular social networks
Possamai, Lino <1978>. "Multidimensional analysis of complex networks". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5389/1/possamai_lino_tesi.pdf.
Texto completoPossamai, Lino <1978>. "Multidimensional analysis of complex networks". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5389/.
Texto completoRingienė, Laura. "Hybrid neural network for multidimensional data visualization". Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140912_140117-42267.
Texto completoŠio darbo tyrimų sritis yra duomenų tyryba remiantis daugiamačių duomenų vizualia analize. Tai leidžia tyrėjui betarpiškai dalyvauti duomenų analizės procese, geriau pažinti sudėtingus duomenis ir priimti geriausius sprendimus. Disertacijos tikslas yra sukurti metodą tokios duomenų projekcijos radimui plokštumoje, kad tyrėjas galėtų pamatyti ir įvertinti daugiamačių taškų tarpgrupinius panašumus/skirtingumus. Šiam tikslui pasiekti yra pasiūlytas radialinių bazinių funkcijų ir daugiasluoksnio perceptrono, turinčio ,,butelio kaklelio“ neuroninio tinklo savybes, junginys. Naujas tinklas naudojamas vizualiai daugiamačių duomenų analizei, kai atidėjimui plokštumoje arba trimatėje erdvėje taškai gaunami paskutinio paslėpto neuronų sluoksnio išėjimuose, kai į tinklo įėjimą paduodami daugiamačiai duomenys. Šio tinklo ypatybė yra ta, kad gautas vaizdas plokštumoje labiau atspindi bendrą duomenų struktūrą (klasteriai, klasterių tarpusavio artumas, taškų tarpklasterinis panašumas) nei daugiamačių taškų tarpusavio išsidėstymą.
Zignani, M. "FROM SMALL-WORLDS TO BIG DATA:TEMPORAL AND MULTIDIMENSIONAL ASPECTS OF HUMAN NETWORKS". Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/233322.
Texto completoLi, Yan. "Multidimensional protein separations in a plastic microfluidic network". College Park, Md. : University of Maryland, 2003. http://hdl.handle.net/1903/194.
Texto completoThesis research directed by: Chemistry. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Suh, Young-Joo. "Realizations of efficient collective communication in multidimensional processor arrays". Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/13343.
Texto completoTulabandula, Sridhar. "Localization of wireless sensor networks using multidimensional scaling". Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4986.
Texto completoThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 17, 2008) Includes bibliographical references.
Sumanasena, M. G. Buddika. "A multidimensional systems approach to grid sensor networks". Thesis, University of Notre Dame, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3578994.
Texto completoA method for distributed information processing in rectangular grid based wireless sensor networks is presented, employing the Givone-Roesser and the Fornasini-Marchesini state space models for m-D systems. It can be used for distributed implementation of any general linear system on a grid sensor network. The method is highly scalable and requires only communication between immediate neighbors.
Usage of finite precision schemes for the representation of numbers and computations introduce nonlinearities to the otherwise linear m-D system models. Nonlinearities caused by fixed point and floating point number representation schemes used for in node computations and inter-node communication are modeled. Stability of the system is analyzed with special consideration given to the influence of inter-node communication on system dynamics. Necessary and sufficient conditions for the global asymptotic stability under both fixed point and floating point arithmetic is derived. It has been shown that the global asymptotic stability of the sensor networks is equivalent to that of a 1-D system for both the cases of fixed point and floating number representation.
Issues posed by communication time delay, in real-time implementation of the proposed method, are discussed. It is shown that, in order to implement a real-time sensor network, system matrices of the state space models have to satisfy certain conditions. A necessary and sufficient condition for a transfer function to be realizable in the constrained state space models is established. Realization algorithms to derive state space models of the desired form given an admissible transfer function are also presented. Node and link failure introduce complications not encountered in centralized implementation of m-D systems. Givone-Roesser and the Fornasini-Marchesini state space models are extended to include node and link failure. Necessary and sufficient conditions for mean square stability are then derived with the help of these two state space models. Input output stability of the distributed systems under node and link failure is also discussed.
The utility of the proposed method is demonstrated by examples. In particular a distributed Kalman filter is proposed for grid sensor networks. Implementation of the proposed Kalman filter on grid sensor networks is discussed in some detail. A method for contaminant detection and its implementation using the proposed method is also presented.
Ahmed, Ahmed Abdol-Monem. "Experimental study of localization in sensor networks and design of adaptive localization". Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/5829.
Texto completoThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (Novembr 15, 2006) Vita. Includes bibliographical references.
Libros sobre el tema "Multidimensionnal network"
Murthy, G. Rama. Multidimensional neural networks: Unified theory. New Delhi: New Age International (P) Ltd., Publishers, 2008.
Buscar texto completoArena, Paolo, Luigi Fortuna, Giovanni Muscato y Maria Gabriella Xibilia, eds. Neural Networks in Multidimensional Domains. London: Springer-Verlag, 1998. http://dx.doi.org/10.1007/bfb0047683.
Texto completoMelikov, Agassi y Leonid Ponomarenko. Multidimensional Queueing Models in Telecommunication Networks. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08669-9.
Texto completoPeer-to-peer query processing over multidimensional data. New York: Springer, 2012.
Buscar texto completoHenderson, Geraldine R. Brand constructs: The complementarity of consumer associative networks and multidimensional scaling. Cambridge, Mass: Marketing Science Institute, 1998.
Buscar texto completoEnvironmental systems: A multidimensional approach. Oxford: Oxford University Press, 2002.
Buscar texto completoHenderson, Geraldine R. Brand constructs: The complementarity of consumer associative networks and multidimensional scaling. Cambridge, Mass: Marketing Science Institute, 1998.
Buscar texto completoE-learning as a socio-cultural system: A multidimensional analysis. Hershey, PA: Information Science Reference, an imprint of IGI Global, 2014.
Buscar texto completoPark, June S. Delay analysis for multidimensional queueing process in CSMA/CD local area networks. Monterey, Calif: Naval Postgraduate School, 1991.
Buscar texto completoVarlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.
Texto completoCapítulos de libros sobre el tema "Multidimensionnal network"
Graves, Alex. "Multidimensional Networks". En Studies in Computational Intelligence, 95–108. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24797-2_8.
Texto completoLu, Rongxing. "Privacy-Preserving Multidimensional Data Aggregation". En Wireless Networks, 41–60. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32899-7_3.
Texto completoDzemyda, Gintautas, Olga Kurasova y Julius Žilinskas. "Combining Multidimensional Scaling with Artificial Neural Networks". En Multidimensional Data Visualization, 113–77. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0236-8_4.
Texto completoChouchane, Amani, Oualid Boutemine y Mohamed Bouguessa. "On Detecting Multidimensional Communities". En Lecture Notes in Social Networks, 45–78. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11286-8_3.
Texto completoJohnson, Jeffrey. "The Multidimensional Networks of Complex Systems". En Networks in Action, 49–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-57843-4_3.
Texto completoAraújo, Tanya y Sven Banisch. "Multidimensional Analysis of Linguistic Networks". En Understanding Complex Systems, 107–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-47238-5_5.
Texto completoKazienko, Przemysław, Katarzyna Musial, Elżbieta Kukla, Tomasz Kajdanowicz y Piotr Bródka. "Multidimensional Social Network: Model and Analysis". En Computational Collective Intelligence. Technologies and Applications, 378–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23935-9_37.
Texto completoGao, Zhenfeng y Guodong Shan. "Billing System and 5G Network Slicing Service". En New Approaches for Multidimensional Signal Processing, 289–97. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8558-3_24.
Texto completoShi, Yansong, Shiyou Xing, Peijian Wang y Dai Jiawei. "Neural Network Algorithm Applied in Electrical Engineering Automation". En New Approaches for Multidimensional Signal Processing, 143–50. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-7842-5_13.
Texto completoMelikov, Agassi y Leonid Ponomarenko. "Priority Schemes in Packet Switching Networks". En Multidimensional Queueing Models in Telecommunication Networks, 141–86. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08669-9_5.
Texto completoActas de conferencias sobre el tema "Multidimensionnal network"
Sharony, Jacob y Yao Li. "Multidimensional broadcast networks". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/oam.1993.wx.5.
Texto completoWang, Mingxian, Wei Chen, Yun Huang, Noshir S. Contractor y Yan Fu. "A Multidimensional Network Approach for Modeling Customer-Product Relations in Engineering Design". En ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46764.
Texto completoLiu, Xuejun, Shuigeng Zhou, Guangwei Bai y Diwen Zhu. "Multidimensional Similarity In-network Query for Large-Scale Sensor Networks". En 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware. IEEE, 2009. http://dx.doi.org/10.1109/mdm.2009.45.
Texto completoDabideen, S. y J. J. Garcia-Luna-Aceves. "Multidimensional Routing". En 17th International Conference on Computer Communications and Networks 2008. IEEE, 2008. http://dx.doi.org/10.1109/icccn.2008.ecp.113.
Texto completoKhaniev, R. E. y S. A. K. Diane. "3D Approach to Visualization of Error Function in the Neural Network Tuning Problem". En 33rd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2023. http://dx.doi.org/10.20948/graphicon-2023-371-376.
Texto completoCorbisiero, Fabio y Antonella Avolio. "Migrazioni e networks urbani". En International Conference Virtual City and Territory. Roma: Centre de Política de Sòl i Valoracions, 2014. http://dx.doi.org/10.5821/ctv.7987.
Texto completoBerlingerio, Michele, Michele Coscia, Fosca Giannotti, Anna Monreale y Dino Pedreschi. "Foundations of Multidimensional Network Analysis". En 2011 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2011). IEEE, 2011. http://dx.doi.org/10.1109/asonam.2011.103.
Texto completoGuha, Rupkatha y S. K. Setua. "A Multidimensional secured network model". En 2013 3rd International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2013. http://dx.doi.org/10.1109/iccsnt.2013.6967259.
Texto completoHealey, Peter, Steven A. Cassidy y David W. Smith. "Multidimensional optical interconnection networks". En OE/LASE '90, 14-19 Jan., Los Angeles, CA, editado por Raymond Arrathoon. SPIE, 1990. http://dx.doi.org/10.1117/12.18063.
Texto completoQuintuna, Veronica y Maxime Laye. "Modeling and optimization of Content Delivery Networks with heuristics solutions for the Multidimensional Knapsack Problem". En 2016 17th International Telecommunications Network Strategy and Planning Symposium (Networks). IEEE, 2016. http://dx.doi.org/10.1109/netwks.2016.7751146.
Texto completoInformes sobre el tema "Multidimensionnal network"
Park, June S. y Keebom Kang. Delay Analysis for Multidimensional Queueing Process in CSMA/CD Local Area Networks. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 1991. http://dx.doi.org/10.21236/ada242364.
Texto completoSoloviev, Volodymyr Mykolayovych y Viktoriya Volodymyrivna Solovyova. Universal tools of modeling different nature complex systems. ФОП Однорог Т.В., 2018. http://dx.doi.org/10.31812/123456789/2865.
Texto completoLi, Jing. Various New Statistical Models for Modeling and Change Detection in Multidimensional Dynamic Networks. Fort Belvoir, VA: Defense Technical Information Center, enero de 2014. http://dx.doi.org/10.21236/ada606729.
Texto completoJohnson, Joseph E. y Vladimir Gudkov. Cyberspace Assurance Metrics: Utilizing Models of Networks, Complex Systems Theory, Multidimensional Wavelet Analysis, and Generalized Entrophy Measures. Fort Belvoir, VA: Defense Technical Information Center, abril de 2005. http://dx.doi.org/10.21236/ada434351.
Texto completoRamm-Granberg, Tynan, F. Rocchio, Catharine Copass, Rachel Brunner y Eric Nelsen. Revised vegetation classification for Mount Rainier, North Cascades, and Olympic national parks: Project summary report. National Park Service, febrero de 2021. http://dx.doi.org/10.36967/nrr-2284511.
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