Auswahl der wissenschaftlichen Literatur zum Thema „Ordered Weights Average“
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Zeitschriftenartikel zum Thema "Ordered Weights Average"
Espinoza-Audelo, Luis F., Ernesto León-Castro, Marycruz Olazabal-Lugo, José M. Merigó und Anna M. Gil-Lafuente. „Using Ordered Weighted Average for Weighted Averages Inflation“. International Journal of Information Technology & Decision Making 19, Nr. 02 (März 2020): 601–28. http://dx.doi.org/10.1142/s0219622020500066.
Der volle Inhalt der QuelleS, Charles, und Dr L. Arockiam. „Fuzzy Weighted Ordered Weighted Average-Gaussian Mixture Model for Feature Reduction“. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, Nr. 2 (30.11.2005): 694–712. http://dx.doi.org/10.24297/ijct.v4i2c2.4192.
Der volle Inhalt der QuelleRuiz-Morales, Betzabe, Irma Cristina Espitia-Moreno, Victor G. Alfaro-Garcia und Ernesto Leon-Castro. „Sustainable Development Goals Analysis with Ordered Weighted Average Operators“. Sustainability 13, Nr. 9 (07.05.2021): 5240. http://dx.doi.org/10.3390/su13095240.
Der volle Inhalt der QuelleYoshida, Yuji. „Ordered Weighted Averages on Intervals and the Sub/Super-Additivity“. Journal of Advanced Computational Intelligence and Intelligent Informatics 17, Nr. 4 (20.07.2013): 520–25. http://dx.doi.org/10.20965/jaciii.2013.p0520.
Der volle Inhalt der QuelleSavarimuthu, Charles, und Arockiam L. „Pairwise Fuzzy Ordered Weighted Average Algorithm-Gaussian Mixture Model for Feature Reduction“. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 6, Nr. 1 (30.05.2013): 287–301. http://dx.doi.org/10.24297/ijct.v6i1.4457.
Der volle Inhalt der QuelleOgryczak, Włodzimierz. „Reference Point Method with Importance Weighted Partial Achievements“. Journal of Telecommunications and Information Technology, Nr. 4 (26.06.2023): 17–25. http://dx.doi.org/10.26636/jtit.2008.4.893.
Der volle Inhalt der QuelleKuz’mina, N. E., S. V. Moiseev, V. I. Krylov, V. A. Yashkir und V. A. Merkulov. „Quantitative determination of the average molecular weights of dextrans by diffusion ordered NMR spectroscopy“. Journal of Analytical Chemistry 69, Nr. 10 (21.09.2014): 953–59. http://dx.doi.org/10.1134/s1061934814100086.
Der volle Inhalt der QuelleWankhade, Sandeep, Manoj Sahni, Cristhian Mellado-Cid und Ernesto Leon-Castro. „Using the Ordered Weighted Average Operator to Gauge Variation in Agriculture Commodities in India“. Axioms 12, Nr. 10 (18.10.2023): 985. http://dx.doi.org/10.3390/axioms12100985.
Der volle Inhalt der QuelleFreixas, Josep. „An Aggregation Rule Based on the Binomial Distribution“. Mathematics 10, Nr. 23 (23.11.2022): 4418. http://dx.doi.org/10.3390/math10234418.
Der volle Inhalt der QuelleMajdan, Michał. „On Subjective Trust Management“. Journal of Telecommunications and Information Technology, Nr. 4 (26.06.2023): 26–31. http://dx.doi.org/10.26636/jtit.2008.4.894.
Der volle Inhalt der QuelleDissertationen zum Thema "Ordered Weights Average"
Vo, Thi Quynh Trang. „Algorithms and Machine Learning for fair and classical combinatorial optimization“. Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2024. http://www.theses.fr/2024UCFA0035.
Der volle Inhalt der QuelleCombinatorial optimization is a field of mathematics that searches for an optimal solution in a finite set of objects. It has crucial applications in many fields, including applied mathematics, software engineering, theoretical computer science, and machine learning. extit{Branch-and-cut} is one of the most widely-used algorithms for solving combinatorial optimization problems exactly. In this thesis, we focus on the computational aspects of branch-and-cut when studying two critical dimensions of combinatorial optimization: extit{the fairness of solutions} and extit{the integration of machine learning}.In Partef{part:1} (Chaptersef{chap:bnc-btsp} andef{chap:owa}), we study two common approaches to deal with the issue of fairness in combinatorial optimization, which has gained significant attention in the past decades. The first approach is extit{balanced combinatorial optimization}, which finds a fair solution by minimizing the difference between the largest and smallest components used. Due to the difficulties in bounding these components, to the best of our knowledge, no general exact framework based on mixed-integer linear programming (MILP) has been proposed for balanced combinatorial optimization. To address this gap, in Chapteref{chap:bnc-btsp}, we present a branch-and-cut algorithm and a novel class of local cutting planes tailored for balanced combinatorial optimization problems. We demonstrate the effectiveness of the proposed framework in the Balanced Traveling Salesman Problem. Additionally, we introduce bounding algorithms and mechanisms to fix variables to accelerate performance further.The second approach to handling the issue of fairness is extit{Ordered Weighted Average (OWA) combinatorial optimization}, which integrates the OWA operator into the objective function. Due to the ordering operator, OWA combinatorial optimization is nonlinear, even if its original constraints are linear. Two MILP formulations of different sizes have been introduced in the literature to linearize the OWA operator. However, which formulation performs best for OWA combinatorial optimization remains uncertain, as integrating the linearization methods may introduce additional difficulties. In Chapteref{chap:owa}, we provide theoretical and empirical comparisons of the two MILP formulations for OWA combinatorial optimization. In particular, we prove that the formulations are equivalent in terms of the linear programming relaxation. We empirically show that for OWA combinatorial optimization problems, the formulation with more variables can be solved faster with branch-and-cut.In Partef{part:2} (Chapteref{chap:mlbnc}), we develop methods for applying machine learning to enhance fundamental decision problems in branch-and-cut, with a focus on cut generation. Cut generation refers to the decision of whether to generate cuts or to branch at each node of the search tree. We empirically demonstrate that this decision significantly impacts branch-and-cut performance, especially for combinatorial cuts that exploit the facial structure of the convex hull of feasible solutions. We then propose a general framework combining supervised and reinforcement learning to learn effective strategies for generating combinatorial cuts in branch-and-cut. Our framework has two components: a cut detector to predict cut existence and a cut evaluator to choose between generating cuts and branching. Finally, we provide experimental results showing that the proposed method outperforms commonly used strategies for cut generation, even on instances larger than those used for training
Colliri, Tiago Santos. „Avaliação de preços de ações: proposta de um índice baseado nos preços históricos ponderados pelo volume, por meio do uso de modelagem computacional“. Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/100/100132/tde-07072013-015903/.
Der volle Inhalt der QuelleThe importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.
Bücher zum Thema "Ordered Weights Average"
Horing, Norman J. Morgenstern. Thermodynamic Green’s Functions and Spectral Structure. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0007.
Der volle Inhalt der QuelleBack, Kerry E. Alternative Preferences. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0025.
Der volle Inhalt der QuelleSkiba, Grzegorz. Fizjologiczne, żywieniowe i genetyczne uwarunkowania właściwości kości rosnących świń. The Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences, 2020. http://dx.doi.org/10.22358/mono_gs_2020.
Der volle Inhalt der QuelleBuchteile zum Thema "Ordered Weights Average"
León-Castro, Ernesto, Fabio Blanco-Mesa und José M. Merigó. „Weighted Averages in the Ordered Weighted Average Inflation“. In Advances in Intelligent Systems and Computing, 87–95. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21920-8_8.
Der volle Inhalt der QuelleWu, Dongrui, und Jian Huang. „Ordered Novel Weighted Averages“. In Type-2 Fuzzy Logic and Systems, 25–47. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72892-6_2.
Der volle Inhalt der QuelleYoshida, Yuji. „An Ordered Weighted Average with a Truncation Weight on Intervals“. In Modeling Decisions for Artificial Intelligence, 45–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34620-0_6.
Der volle Inhalt der QuelleCornelis, Chris, Nele Verbiest und Richard Jensen. „Ordered Weighted Average Based Fuzzy Rough Sets“. In Lecture Notes in Computer Science, 78–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16248-0_16.
Der volle Inhalt der QuelleKlimo, Martin, Ondrej Škvarek, Juraj Smieško, Stanislav Foltán und Ondrej Šuch. „Vowel Recognition Supported by Ordered Weighted Average“. In Advances in Intelligent Systems and Computing, 247–53. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10783-7_27.
Der volle Inhalt der QuelleMitchell, H. B. „Data Mining Using a Probabilistic Weighted Ordered Weighted Average (PWOWA) Operator“. In Information Fusion in Data Mining, 41–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36519-8_4.
Der volle Inhalt der QuelleShams, Parham, Aurélie Beynier, Sylvain Bouveret und Nicolas Maudet. „Minimizing and Balancing Envy Among Agents Using Ordered Weighted Average“. In Algorithmic Decision Theory, 289–303. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87756-9_19.
Der volle Inhalt der QuelleKacprzyk, Janusz, und Mario Fedrizzi. „Consensus Degrees Under Fuzziness via Ordered Weighted Average (OWA) Operators“. In Fuzzy Logic and its Applications to Engineering, Information Sciences, and Intelligent Systems, 447–53. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-009-0125-4_44.
Der volle Inhalt der QuelleMerigó, José M., Montserrat Guillén und José M. Sarabia. „A Generalization of the Variance by Using the Ordered Weighted Average“. In Modeling and Simulation in Engineering, Economics, and Management, 222–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38279-6_24.
Der volle Inhalt der QuelleVerbiest, Nele, Chris Cornelis und Francisco Herrera. „OWA-FRPS: A Prototype Selection Method Based on Ordered Weighted Average Fuzzy Rough Set Theory“. In Lecture Notes in Computer Science, 180–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41218-9_19.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Ordered Weights Average"
Darmstadt, Patrick, und Mark Robuck. „Composites for Advanced Drive Systems, a Systems Analysis Revolutionary Vertical Lift Technology (RVLT)“. In Vertical Flight Society 74th Annual Forum & Technology Display, 1–16. The Vertical Flight Society, 2018. http://dx.doi.org/10.4050/f-0074-2018-12862.
Der volle Inhalt der QuelleWhalen, Thomas. „Additive Weighted Ordered Weighted Average“. In NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society. IEEE, 2007. http://dx.doi.org/10.1109/nafips.2007.383871.
Der volle Inhalt der QuelleWu, Dongrui, und Jerry M. Mendel. „Ordered fuzzy weighted averages and ordered linguistic weighted averages“. In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584479.
Der volle Inhalt der QuelleMarin, Lucas, Jose M. Merigo, Aida Valls, Antonio Moreno und David Isern. „Induced Unbalanced Linguistic Ordered Weighted Average“. In 7th conference of the European Society for Fuzzy Logic and Technology. Paris, France: Atlantis Press, 2011. http://dx.doi.org/10.2991/eusflat.2011.88.
Der volle Inhalt der QuelleMerigo, Jose M., Nabil Alrajeh und Marta Peris-Ortiz. „Induced aggregation operators in the ordered weighted average sum“. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2016. http://dx.doi.org/10.1109/ssci.2016.7850148.
Der volle Inhalt der QuelleVo, Thi Quynh Trang, Mourad Baiou, Viet Hung Nguyen und Paul Weng. „A comparative study of linearization methods for Ordered Weighted Average“. In 2022 12th International Workshop on Resilient Networks Design and Modeling (RNDM). IEEE, 2022. http://dx.doi.org/10.1109/rndm55901.2022.9927720.
Der volle Inhalt der QuelleMeenachi, L., J. Jayanth Raghul, C. Mohan Raj und B. Kathiravan. „Diagnosis of medical dataset using fuzzy-rough ordered weighted average classification“. In 2017 4th International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS). IEEE, 2017. http://dx.doi.org/10.1109/iciiecs.2017.8275922.
Der volle Inhalt der QuelleHai Wang, Yan Zhang und Gang Qian. „Multiple binary classifiers fusion using induced intuitionistic fuzzy ordered weighted average operator“. In 2011 International Conference on Information and Automation (ICIA). IEEE, 2011. http://dx.doi.org/10.1109/icinfa.2011.5948993.
Der volle Inhalt der QuelleDinh, My H., James Kotary und Ferdinando Fioretto. „Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages“. In FAccT '24: The 2024 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3630106.3661932.
Der volle Inhalt der QuelleZhao, Xinye, Xiaowei Zhang, Wenming Zhang und Fan Yang. „Some induced generalized ordered weighted power average operators within intuitionistic trapezoidal fuzzy setting“. In 2016 12th International Conference on Natural Computation and 13th Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2016. http://dx.doi.org/10.1109/fskd.2016.7603301.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Ordered Weights Average"
Zhang, Hongbin B., David J. Bonfil und Shahal Abbo. Genomics Tools for Legume Agronomic Gene Mapping and Cloning, and Genome Analysis: Chickpea as a Model. United States Department of Agriculture, März 2003. http://dx.doi.org/10.32747/2003.7586464.bard.
Der volle Inhalt der QuelleMizrach, Amos, Sydney L. Spahr, Ephraim Maltz, Michael R. Murphy, Zeev Schmilovitch, Jan E. Novakofski, Uri M. Peiper et al. Ultrasonic Body Condition Measurements for Computerized Dairy Management Systems. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568109.bard.
Der volle Inhalt der QuelleJob, Jacob. Mesa Verde National Park: Acoustic monitoring report. National Park Service, Juli 2021. http://dx.doi.org/10.36967/nrr-2286703.
Der volle Inhalt der QuelleMaycock, Barry, Cath Mulholland, Emma French und Joseph Shavila. Rapid Risk Assessment: What is the risk from microcystins in the edible flesh of fish caught from Lough Neagh? Food Standards Agency, März 2024. http://dx.doi.org/10.46756/sci.fsa.slz868.
Der volle Inhalt der QuelleIntroduction Success of Less Common Species from the Genus Berberis L. Ukrainian Journal of Ecology, 2019. http://dx.doi.org/10.31812/123456789/3641.
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