Teses / dissertações sobre o tema "Online algorithm with advice"
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Renault, Marc Paul. "Lower and upper bounds for online algorithms with advice". Paris 7, 2014. http://www.theses.fr/2014PA077196.
Texto completo da fonteOnline algorithms operate in a setting where the input is revealed piece by piece; the pieces are called requests. After receiving each request, online algorithms must take an action before the next request is revealed, i. E. Online algorithms must make irrevocable decisions based on the input revealed so far without any knowledge of the future input. The goal is to optimize some cost function over the input. Competitive analysis is the standard method used to analyse the quality of online algorithms. The competitive ratio is the worst case ratio, over all valid finite request sequences, of the online algorithm's performance against an optimal offline algorithm for the same request sequence. The competitive ratio compares the performance of an algorithm with no knowledge about the future against an algorithm with full knowledge about the future. Since the complete absence of future knowledge is often not a reasonable assumption, models, termed online algorithms with advice, which give the online algorithms access to a quantified amount of future knowledge, have been proposed. The interest in this model is in examining how the competitive ratio changes as a function of the amount of advice. In this thesis, we present upper and lower bounds in the advice model for classical online problems such as the k-server problem, the bin packing problem, the dual bin packing (multiple knapsack) problem, scheduling problem on m identical machines, the reordering buffer management problem and the list update problem
Jin, Shendan. "Online computation beyond standard models". Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS152.
Texto completo da fonteIn the standard setting of online computation, the input is not entirely available from the beginning, but is revealed incrementally, piece by piece, as a sequence of requests. Whenever a request arrives, the online algorithm has to make immediately irrevocable decisions to serve the request, without knowledge on the future requests. Usually, the standard framework to evaluate the performance of online algorithms is competitive analysis, which compares the worst-case performance of an online algorithm to an offline optimal solution. In this thesis, we will study some new ways of looking at online problems. First, we study the online computation in the recourse model, in which the irrevocability on online decisions is relaxed. In other words, the online algorithm is allowed to go back and change previously made decisions. More precisely, we show how to identify the trade-off between the number of re-optimization and the performance of online algorithms for the online maximum matching problem. Moreover, we study measures other than competitive analysis for evaluating the performance of online algorithms. We observe that sometimes, competitive analysis cannot distinguish the performance of different algorithms due to the worst-case nature of the competitive ratio. We demonstrate that a similar situation arises in the linear search problem. More precisely, we revisit the linear search problem and introduce a measure, which can be applied as a refinement of the competitive ratio. Last, we study the online computation in the advice model, in which the algorithm receives as input not only a sequence of requests, but also some advice on the request sequence. Specifically, we study a recent model with untrusted advice, in which the advice can be either trusted or untrusted. Assume that in the latter case, the advice can be generated from a malicious source. We show how to identify a Pareto optimal strategy for the online bidding problem in the untrusted advice model
Cayuela, Rafols Marc. "Algorithmic Study on Prediction with Expert Advice : Study of 3 novel paradigms with Grouped Experts". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254344.
Texto completo da fonteHuvudarbetet för den här avhandlingen har varit en grundlig studie av den nya Prediction with Partially Monitored Grouped Expert Advice and Side Information paradigmet. Detta är nyligen föreslagit i denna avhandling, och det utökar det brett studerade Prediction with Expert Advice paradigmet. Förlängningen baseras på två antaganden och en begränsning som ändrar det ursprungliga problemet. Det första antagandet, Grouped, förutsätter att experterna är inbyggda i grupper. Det andra antagandet, Side Information, introducerar ytterligare information som kan användas för att i tid relatera förutsägelser med grupper. Slutligen innebär begränsningen, Partially Monitored, att gruppens förutsägelser endast är kända för en grupp i taget. Studien av detta paradigm innefattar utformningen av en komplett förutsägelsesalgoritm, beviset på en teoretisk bindning till det sämre fallet kumulativa ånger för en sådan algoritm och en experimentell utvärdering av algoritmen (bevisar förekomsten av fall där detta paradigm överträffar Prediction with Expert Advice). Eftersom algoritmens utveckling är konstruktiv tillåter den dessutom att enkelt bygga två ytterligare prediksionsalgoritmer för Prediction with Grouped Expert Advice och Prediction with Grouped Expert Advice and Side Information paradigmer. Därför presenterar denna avhandling tre nya prediktionsalgoritmer med motsvarande ångergränser och en jämförande experimentell utvärdering inklusive det ursprungliga Prediction with Expert Advice paradigmet.
Henke, Hans-Christian. "Online Advice : Konzeption eines ergebnisbasierten Simulationsansatzes /". [S.l. : s.n.], 2003. http://www.gbv.de/dms/zbw/362397171.pdf.
Texto completo da fonteFurkin, Jennifer D. "MOM TO MOM: ONLINE BREASTFEEDING ADVICE". UKnowledge, 2018. https://uknowledge.uky.edu/comm_etds/64.
Texto completo da fontePorter, Noriko. "Japanese and U. S. mother's concerns and experts' advice content analysis of mothers' questions on online message boards and experts' advice in parenting magazines /". Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/5517.
Texto completo da fonteThe 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 June 15, 2009) Vita. Includes bibliographical references.
Fowler-Dawson, Amy E. "Expand your online reach with these 10 social media tips from the pros: An analysis of online social networking advice". OpenSIUC, 2016. https://opensiuc.lib.siu.edu/theses/2047.
Texto completo da fonteBarbaro, Billy. "Tuning Hyperparameters for Online Learning". Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1522419008006144.
Texto completo da fonteMurphy, Nicholas John. "An online learning algorithm for technical trading". Master's thesis, Faculty of Science, 2019. http://hdl.handle.net/11427/31048.
Texto completo da fonteOrlansky, Emily. "Beauty is in the mouth of the beholder advice networks at Haverford College /". Diss., Connect to the thesis, 2009. http://hdl.handle.net/10066/3707.
Texto completo da fonteHiller, Benjamin [Verfasser]. "Online Optimization: Probabilistic Analysis and Algorithm Engineering / Benjamin Hiller". München : Verlag Dr. Hut, 2012. http://d-nb.info/1025821319/34.
Texto completo da fonteLaflamme, Simon M. Eng Massachusetts Institute of Technology. "Online learning algorithm for structural control using magnetorheological actuators". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39271.
Texto completo da fonteIncludes bibliographical references (p. 83-84).
Magnetorheological actuators are promising devices for mitigating vibrations because they only require a fraction of energy for a similar performance to active control. Conversely, these semi-active devices have limited maximum forces and are hard to model due to the rheological properties of their fluid. When considering structural control, classical theories necessitate full knowledge of the structural dynamic states and properties most of which can only be estimated when considering large-scale control, which may be difficult or inaccurate for complicated geometries due to the non-linear behaviour of structures. Additionally, most of these theories do not take into account the response delay of the actuators which may result in structural instabilities. To address the problem, learning algorithms using offline learning have been proposed in order to have the structure learn its behaviour, but they can be perceived as unrealistic because earthquake data can hardly be produced to train these schemes. Here, an algorithm using online learning feedback is proposed to address this problem where the structure observes, compares and adapts its performance at each time step, analogous to a child learning his or her motor functions.
(cont.) The algorithm uses a machine learning technique, Gaussian kernels, to prescribe forces upon structural states, where states are evaluated strictly based on displacement and acceleration feedback. The algorithm has been simulated and performances assessed by comparing it with two classical control theories: clipped-optimal and passive controls. The proposed scheme is found to be stable and performs well in mitigating vibrations for a low energy input, but does not perform as well compared to clipped-optimal case. This relative performance would be expected to be better for large-scale structures because of the adaptability of the proposed algorithm.
by Simon Laflamme.
M.Eng.
Bozorgmehr, Pouya. "An efficient online feature extraction algorithm for neural networks". Diss., [La Jolla] : University of California, San Diego, 2009. http://wwwlib.umi.com/cr/ucsd/fullcit?p1470604.
Texto completo da fonteTitle from first page of PDF file (viewed January 13, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 61-63).
Vitiello, Thomas. "Peeking on the campaign : online Voting Advice Applications : challenges and prospects for electoral studies in the digital era". Thesis, Paris, Institut d'études politiques, 2018. http://www.theses.fr/2018IEPP0001/document.
Texto completo da fonteOnline Voting Advice Applications (VAAs) are websites or online applications that show voters which party or candidate is closest to their own political ideas based on how they mark their positions on an ample range of policy issues. In addition to providing voters with reliable information in a structured manner, VAAs are an innovative data-collection tool on issue positions and on a wide set of other indicators. The main scope of this dissertation is to use VAA-collected data to learn about online information exposure during campaigns across media systems. Building on the realistic view of the Web’s political potential and its impact on the public, this dissertation test the hypothesis that VAA use by different voter groups (partisan, doubting and undecided voters) varies across media systems. The analyses of VAA-collected data in seven electoral democracies across three different types of media systems (Democratic Corporatist, Liberal, and Polarized Pluralist) show that media systems are key mediators to explain online information exposure. The second scope of this dissertation is to use VAA-collected data for the sake of electoral analysis, in particular to study issue-voting and campaign dynamics analyses. Several analyses are carried out using data collected by the French VAA of La Boussole présidentielle. This dissertation shows that, despite being non-probabilistic, VAA samples can serve as a very informative tool for the study of political and communication processes during electoral campaigns if integrated within an appropriate research framework and with the use of proper statistical adjustment
Kaplunovich, Petr A. (Petr Alexandrovich). "Efficient algorithm for online N - 2 power grid contingency selection". Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/88388.
Texto completo da fonteCataloged from PDF version of thesis.
Includes bibliographical references (pages 55-57).
Multiple element outages (N - k contingencies) have caused some of the most massive blackouts and disturbances in the power grid. Such outages affect millions of people and cost the world economy billions of dollars annually. The impact of the N - k contingencies is anticipated to grow as the electrical power grid becomes increasingly more loaded. As the result power system operators face the need for advanced techniques to select and mitigate high order contingencies. This study presents a novel algorithm for the fast N - 2 contingency selection to address this problem. The developed algorithm identifies all potentially dangerous contingencies with zero missing rate. The complexity of the algorithm is shown to be of the same order as the complexity of N - 1 contingency selection, which makes it much more efficient than brute force enumeration. The study first derives the equations describing the set of the dangerous N - 2 contingencies in the symmetric form and presents an effective way to bound them. The derived bounding technique is then used to develop an iterative pruning algorithm. Next, the performance of the algorithm is validated using various grid cases under different load conditions. The efficiency of the algorithm is shown to be rather promising. For the Summer Polish grid case with more than 3500 lines it manages to reduce the size of the contingency candidates set by the factor of 1000 in just 2 iterations. Finally, the reasons behind the efficiency of the algorithm are discussed and intuition around the connection of its performance to the grid structure is provided.
by Petr A. Kaplunovich.
S.M.
Zhang, Xiaoyu. "Effective Search in Online Knowledge Communities: A Genetic Algorithm Approach". Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/35059.
Texto completo da fonteMaster of Science
Lövgren, Tobias. "Kostråd på internet : En tvärsnittsstudie bland unga vuxna". Thesis, Högskolan i Gävle, Avdelningen för arbets- och folkhälsovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-19706.
Texto completo da fonteSammanfattning Denna studie syftade till att identifiera unga vuxnas källor till kostråd på internet och hur de upplevde trovärdigheten av dessa. Studien syftade även till att undersöka unga vuxnas kännedom om Livsmedelsverkets näringsrekommendationer En webbaserad enkätundersökning distribuerades via det sociala mediet Facebook. Enkätens formulär innehöll totalt 14 frågor om kostråd på internet och dess trovärdighet. Slutligen efterfrågades respondentens kännedom och i förekommande fall, trovärdigheten av Livsmedelsverkets näringsrekommendationer. Undersökningen fick snabbt en stor spridning och 302 respondenter mellan 20 och 30 år deltog i undersökningen. Studiens resultat visade att 59 procent av respondenterna sökte efter kostråd på internet. Det var en större andel kvinnor än män som sökte, dessutom sökte kvinnorna mer frekvent. Den främsta källan till kostråd på internet bland respondenterna var bloggar. Den upplevda trovärdigheten för bloggar var relativt hög. Det främsta syftet för att söka efter kostråd på internet var viktnedgång för kvinnor och muskelökning för män. Studien visade även att 67 procent av respondenterna kände till Livsmedelsverkets näringsrekommendationer. Den upplevda trovärdigheten för Livsmedelsverkets näringsrekommendationer var högre än den upplevda trovärdigheten för de främsta källorna till kostråd på internet. Denna studie visar att internet är ett kraftfullt verktyg i skapandet av unga vuxnas identitet och även när det gäller påverkan av deras syn på hälsosamma matvanor. Det är av stor betydelse för den framtida folkhälsan att politiker och hälsovårdande myndigheter finner och förstår sin roll i det moderna informationssamhället.
Witney, Cynthia Ann. "Just a “Click” away from evidence-based online breast cancer information, advice and support provided by a specialist nurse: An ethnonetnographic study". Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2015. https://ro.ecu.edu.au/theses/1679.
Texto completo da fonteGagliolo, Matteo. "Online Dynamic Algorithm Portfolios: Minimizing the computational cost of problem solving". Doctoral thesis, Università della Svizzera italiana, Lugano, Switzerland, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/250787.
Texto completo da fontePermanent URL: http://doc.rero.ch/record/20245
info:eu-repo/semantics/nonPublished
Jankovic, Anja. "Towards Online Landscape-Aware Algorithm Selection in Numerical Black-Box Optimization". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS302.
Texto completo da fonteBlack-box optimization algorithms (BBOAs) are conceived for settings in which exact problem formulations are non-existent, inaccessible, or too complex for an analytical solution. BBOAs are essentially the only means of finding a good solution to such problems. Due to their general applicability, BBOAs can exhibit different behaviors when optimizing different types of problems. This yields a meta-optimization problem of choosing the best suited algorithm for a particular problem, called the algorithm selection (AS) problem. By reason of inherent human bias and limited expert knowledge, the vision of automating the selection process has quickly gained traction in the community. One prominent way of doing so is via so-called landscape-aware AS, where the choice of the algorithm is based on predicting its performance by means of numerical problem instance representations called features. A key challenge that landscape-aware AS faces is the computational overhead of extracting the features, a step typically designed to precede the actual optimization. In this thesis, we propose a novel trajectory-based landscape-aware AS approach which incorporates the feature extraction step within the optimization process. We show that the features computed using the search trajectory samples lead to robust and reliable predictions of algorithm performance, and to powerful algorithm selection models built atop. We also present several preparatory analyses, including a novel perspective of combining two complementary regression strategies that outperforms any of the classical, single regression models, to amplify the quality of the final selector
Alon, Alexander Joel Dacara. "The AlgoViz Project: Building an Algorithm Visualization Web Community". Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/34246.
Texto completo da fonteMaster of Science
Goemans, Michel X., Maurice Queyranne, Andreas S. Schulz, Martin Skutella e Yaoguang Wang. "Single Machine Scheduling with Release Dates". Massachusetts Institute of Technology, Operations Research Center, 1999. http://hdl.handle.net/1721.1/5211.
Texto completo da fonteBoccalini, Gabriele. "An optical sensor for online hematocrit measurement: characterization and fitting algorithm development". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6932/.
Texto completo da fonteZubeir, Abdulghani Ismail. "OAP: An efficient online principal component analysis algorithm for streaming EEG data". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-392403.
Texto completo da fonteKnight, Melissa. "Accelerated Online and Hybrid RN-to-BSN Programs: A Predictive Retention Algorithm". ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6345.
Texto completo da fonteStummer, Gudrun. "A reflexive action research project to investigate the development of an educational public health website with an integrated online advice service". Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500798.
Texto completo da fonteVlasenko, Anton. "Developing and Evaluating Web Marking Tools as a Complementary Service for Medical Telephone-Based Advice-Giving". Thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-69498.
Texto completo da fonteFarghally, Mohammed Fawzi Seddik. "Visualizing Algorithm Analysis Topics". Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73539.
Texto completo da fontePh. D.
Deane, Jason. "Scheduling online advertisements using information retrieval and neural network/genetic algorithm based metaheuristics". [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0015400.
Texto completo da fonteProvatas, Spyridon. "An Online Machine Learning Algorithm for Heat Load Forecasting in District Heating Systems". Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3475.
Texto completo da fonteKamath, Akash S. "An efficient algorithm for caching online analytical processing objects in a distributed environment". Ohio : Ohio University, 2002. http://www.ohiolink.edu/etd/view.cgi?ohiou1174678903.
Texto completo da fonteWithum, David Grant. "Serological testing algorithm for recent HIV 1 seroconversion (STARHS) : standardisation and online application". Thesis, King's College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.249615.
Texto completo da fonteStark, Annegret, e Fritz Hoffmann. "Online-Vorbereitungskurse Mathematik und Physik: Fachlich gut gewappnet ins Studium starten". TUDpress, 2020. https://tud.qucosa.de/id/qucosa%3A74306.
Texto completo da fonteNayyar, Krati. "Input Sensitive Analysis of a Minimum Metric Bipartite Matching Algorithm". Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/86518.
Texto completo da fonteMaster of Science
Kuß, Julia, Anja Abdel-Haq, Anne Jacob e Theresia Zimmermann. "Entwicklung von Online-Self-Assessments für Studiengänge der Ingenieurwissenschaften an der TU Dresden". TUDpress, 2020. https://tud.qucosa.de/id/qucosa%3A74310.
Texto completo da fonteChen, Jian. "Maintaining Stream Data Distribution Over Sliding Window". Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-35321.
Texto completo da fonteWedenberg, Kim, e Alexander Sjöberg. "Online inference of topics : Implementation of the topic model Latent Dirichlet Allocation using an online variational bayes inference algorithm to sort news articles". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-222429.
Texto completo da fonteJaradat, Shatha. "OLLDA: Dynamic and Scalable Topic Modelling for Twitter : AN ONLINE SUPERVISED LATENT DIRICHLET ALLOCATION ALGORITHM". Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177535.
Texto completo da fonteTillhandahålla högkvalitativa ämnen slutsats i dagens stora och dynamiska korpusar, såsom Twitter, är en utmanande uppgift. Detta är särskilt utmanande med tanke på att innehållet i den här miljön innehåller korta texter och många förkortningar. Projektet föreslår en förbättring med en populär online ämnen modellering algoritm för Latent Dirichlet Tilldelning (LDA), genom att införliva tillsyn för att göra den lämplig för Twitter sammanhang. Denna förbättring motiveras av behovet av en enda algoritm som uppnår båda målen: analysera stora mängder av dokument, inklusive nya dokument som anländer i en bäck, och samtidigt uppnå hög kvalitet på ämnen "upptäckt i speciella fall miljöer, till exempel som Twitter. Den föreslagna algoritmen är en kombination av en online-algoritm för LDA och en övervakad variant av LDA - Labeled LDA. Prestanda och kvalitet av den föreslagna algoritmen jämförs med dessa två algoritmer. Resultaten visar att den föreslagna algoritmen har visat bättre prestanda och kvalitet i jämförelse med den övervakade varianten av LDA, och det uppnådde bättre resultat i fråga om kvalitet i jämförelse med den online-algoritmen. Dessa förbättringar gör vår algoritm till ett attraktivt alternativ när de tillämpas på dynamiska miljöer, som Twitter. En miljö för att analysera och märkning uppgifter är utformad för att förbereda dataset innan du utför experimenten. Möjliga användningsområden för den föreslagna algoritmen är tweets rekommendation och trender upptäckt.
Breakiron, Daniel Aubrey. "Evaluating the Integration of Online, Interactive Tutorials into a Data Structures and Algorithms Course". Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23107.
Texto completo da fonteMaster of Science
Kunwar, Rituraj. "Incremental / Online Learning and its Application to Handwritten Character Recognition". Thesis, Griffith University, 2017. http://hdl.handle.net/10072/366964.
Texto completo da fonteThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information and Communication Technology
Science, Environment, Engineering and Technology
Full Text
Harrington, Edward, e edwardharrington@homemail com au. "Aspects of Online Learning". The Australian National University. Research School of Information Sciences and Engineering, 2004. http://thesis.anu.edu.au./public/adt-ANU20060328.160810.
Texto completo da fonteLuo, Lingzhi. "Distributed Algorithm Design for Constrained Multi-robot Task Assignment". Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/426.
Texto completo da fonteAlim, Sophia. "Vulnerability in online social network profiles : a framework for measuring consequences of information disclosure in online social networks". Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5507.
Texto completo da fonteMahajan, Rutvij Sanjay. "Empirical Analysis of Algorithms for the k-Server and Online Bipartite Matching Problems". Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/96725.
Texto completo da fonteMS
Botha, Marlene. "Online traffic engineering for MPLS networks". Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/50049.
Texto completo da fonteENGLISH ABSTRACT: The Internet is fast evolving into a commercial platform that carries a mixture of narrow- and broadband applications such as voice, video, and data. Users expect a certain level of guaranteed service from their service providers and consequently the need exists for efficient Internet traffic engineering to enable better Quality of Service (QoS) capabilities. Multi-protocol Label Switching (MPLS) is a label switching protocol that has emerged as an enabling technology to achieve efficient traffic engineering for QoS management in IP networks. The ability of the MPLS protocol to create explicit virtual connections called Label Switched Paths (LSPs) to carry network traffic significantly enhances the traffic engineering capabilities of communication networks. The MPLS protocol supports two options for explicit LSP selection: offline LSP computation using an optimization method and dynamic route selection where a single node makes use of current available network state information in order to compute an explicit LSP online. This thesis investigates various methods for the selection of explicit bandwidth guaranteed LSPs through dynamic route selection. We address the problem of computing a sequence of optimal LSPs where each LSP can carry a specific traffic demand and we assume that no prior information regarding the future traffic demands are available and that the arrival sequence of LSP requests to the network is unknown. Furthermore, we investigate the rerouting abilities of the online LSP selection methods to perform MPLS failure restoration upon link failure. We propose a new online routing framework known as Least Interference Optimization (LIO) that utilizes the current bandwidth availability and traffic flow distribution to achieve efficient traffic engineering. We present the Least Interference Optimization Algorithm (LIOA) that reduces the interference among competing network flows by balancing the number and quantity of flows carried by a link for the setup of bandwidth guaranteed LSPs in MPLS networks. The LIOA routing strategy is evaluated and compared against well-known routing strategies such as the Minimum Hop Algorithm (MHA), Minimum Interference Routing Algorithm (MIRA), Open Shortest Path First (OSPF) and Constraint Shortest Path First (CSPF) by means of simulation. Simulation results revealed that, for the network topologies under consideration, the routing strategies that employed dynamic network state information in their routing decisions (LIOA, CSPF and MIRA) generally outperformed the routing strategies that only rely on static network information (OSPF and MHA). In most simulation experiments the best performance was achieved by the LIOA routing strategy while the MHA performed the worse. Furthermore we observed that the computational complexity of the MIRA routing strategy does not translate into equivalent performance gains. We employed the online routing strategies for MPLS failure recovery upon link failure. In particular we investigated two aspects to determine the efficiency of the routing strategies for MPLS rerouting: the suitability of the LSP configuration that results due to the establishment of LSPs prior to link failure and the ability of the online routing strategy to reroute failed LSPs upon link failure. Simulation results revealed similar rerouting performance for all online routing strategies under investigation, but a LSP configuration most suitable for online rerouting was observed for the LIOA routing strategy.
AFRIKAANSE OPSOMMING:Die Internet is voordurend besig om te evoleer in 'n medium wat 'n wye reeks moderne kommunikasietegnologiee ondersteun, insluitende telefoon, video en data. Internet gebruikers verwag gewaarborgde diens van hul diensverskaffers en daar bestaan dus 'n vraag na doeltreffende televerkeerbeheer vir gewaarborgde Internet diensgehalte. Multiprotokol Etiketskakeling (MPLS) is 'n etiketskakeling protokol wat doeltreffende televerkeerbeheer en diensgehalte moontlik maak deur die eksplisiete seleksie van virtuele konneksies vir die transmissie van netwerkverkeer in Internetprotokol (IP) netwerke. Hierdie virtuele konneksies staan bekend as etiketgeskakelde paaie. Die MPLS protokol ondersteun tans twee moontlikhede vir eksplisiete seleksie van etiketgeskakelde paaie: aflyn padberekening met behulp van optimeringsmetodes en dinamiese aanlyn padseleksie waar 'n gekose node 'n eksplisiete pad bereken deur die huidige stand van die netwerk in ag te neem. In hierdie tesis word verskeie padseleksiemetodes vir die seleksie van eksplisiete bandwydte-gewaarborgde etiketgeskakelde paaie deur mid del van dinamiese padseleksie ondersoek. Die probleem om 'n reeks optimale etiketgeskakelde paaie te bereken wat elk 'n gespesifeerde verkeersaanvraag kan akkommodeer word aangespreek. Daar word aanvaar dat geen informasie in verband met die toekomstige verkeersaanvraag bekend is nie en dat die aankomsvolgorde van etiketgeskakelde pad verso eke onbekend is. Ons ondersoek verder die herroeteringsmoontlikhede van die aanlyn padseleksiemetodes vir MPLS foutrestorasie in die geval van skakelonderbreking. Vir hierdie doel word 'n nuwe aanlyn roeteringsraamwerk naamlik Laagste Inwerking Optimering (LIO) voorgestel. LIO benut die huidige beskikbare bandwydte en verkeersvloeidistribusie van die netwerk om doeltreffende televerkeerbeheer moontlik te maak. Ons beskryf 'n Laagste Inwerking Optimering Algoritme (LIOA) wat die inwerking tussen kompeterende verkeersvloei verminder deur 'n balans te handhaaf tussen die aantal en kwantiteit van die verkeersvloeistrome wat gedra word deur elke netwerkskakel. Die LIOA roeteringstrategie word geevalueer met behulp van simulasie en die resultate word vergelyk met ander bekende roeteringstrategiee insluitende die Minimum Node Algorithme (MHA), die Minimum Inwerking Algoritme (MIRA), die Wydste Kortste Pad Eerste Algoritme (OSPF) en die Beperkte Kortste Pad Eerste Algoritme (CSPF). Die resultate van die simulasie-eksperimente to on dat, vir die netwerk topologiee onder eksperimentasie, die roeteringstratgiee wat roeteringsbesluite op dinamiese netwerk informasie baseer (LIOA, MIRA, CSPF) oor die algemeen beter vaar as die wat slegs staatmaak op statiese netwerkinformasie (MHA, OSPF). In die meeste simulasie-eksperimente vaar die LIOA roeteringstrategie die beste en die MHA roeteringstrategie die slegste. Daar word verder waargeneem dat die komputasiekomplesiteit van die MIRA roeteringstrategie nie noodwendig weerspieel word in die sukses van roeteringsuitkoms nie. In die geval waar die aanlyn roeteringstrategiee aangewend word vir MPLS foutrestorasie, toon die resultate van simulasie-eksperimente dat al die roeteringstrategiee min of meer dieselfde uitkoms lewer ten opsigte van herroetering van onderbreekte verkeersvloei. Die konfigurasie van etiketgeskakelde paaie deur die LIOA roeteringstrategie voor skakelonderbreking is egter die geskikste vir televerkeer herroetering na skakelonderbreking
Morimoto, Naoyuki. "Design and Analysis of Algorithms for Graph Exploration and Resource Allocation Problems and Their Application to Energy Management". 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/189687.
Texto completo da fonteCampanini, Alessandro. "Online Parameters Estimation in Battery Systems for EV and PHEV Applications". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
Encontre o texto completo da fonteRaykhel, Ilya Igorevitch. "Real-Time Automatic Price Prediction for eBay Online Trading". BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1631.
Texto completo da fonteHolmgren, Faghihi Josef, e Paul Gorgis. "Time efficiency and mistake rates for online learning algorithms : A comparison between Online Gradient Descent and Second Order Perceptron algorithm and their performance on two different data sets". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260087.
Texto completo da fonteDen här avhandlingen undersöker skillnaden mellan två olika “online learning”-algoritmer: Online Gradient Descent och Second-Order Perceptron, och hur de presterar på olika datasets med fokus på andelen felklassificeringar, tidseffektivitet och antalet uppdateringar. Genom att studera olika “online learning”-algoritmer och hur de fungerar i olika miljöer, kommer det hjälpa till att förstå och utveckla nya strategier för att hantera vidare “online learning”-problem. Studien inkluderar två olika dataset, Pima Indians Diabetes och Mushroom, och använder biblioteket LIBOL för testning. Resultatet i denna avhandling visar att Online Gradient Descent presterar bättre överlag på de testade dataseten. För det första datasetet visade Online Gradient Descent ett betydligt lägre andel felklassificeringar. För det andra datasetet visade OGD lite högre andel felklassificeringar, men samtidigt var algoritmen anmärkningsvärt mer tidseffektiv i jämförelse med Second-Order Perceptron. Framtida studier inkluderar en bredare testning med mer, och olika, datasets och andra relaterade algoritmer. Det leder till bättre resultat och höjer trovärdigheten.
Holm, Raven R. "Natural language processing of online propaganda as a means of passively monitoring an adversarial ideology". Thesis, Monterey, California: Naval Postgraduate School, 2017. http://hdl.handle.net/10945/52993.
Texto completo da fonteReissued 30 May 2017 with Second Reader’s non-NPS affiliation added to title page.
Online propaganda embodies a potent new form of warfare; one that extends the strategic reach of our adversaries and overwhelms analysts. Foreign organizations have effectively leveraged an online presence to influence elections and distance-recruit. The Islamic State has also shown proficiency in outsourcing violence, proving that propaganda can enable an organization to wage physical war at very little cost and without the resources traditionally required. To augment new counter foreign propaganda initiatives, this thesis presents a pipeline for defining, detecting and monitoring ideology in text. A corpus of 3,049 modern online texts was assembled and two classifiers were created: one for detecting authorship and another for detecting ideology. The classifiers demonstrated 92.70% recall and 95.84% precision in detecting authorship, and detected ideological content with 76.53% recall and 95.61% precision. Both classifiers were combined to simulate how an ideology can be detected and how its composition could be passively monitored across time. Implementation of such a system could conserve manpower in the intelligence community and add a new dimension to analysis. Although this pipeline makes presumptions about the quality and integrity of input, it is a novel contribution to the fields of Natural Language Processing and Information Warfare.
Lieutenant, United States Coast Guard