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Bibliographies thématiques / Attractiveness, Stochastic order

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Littérature scientifique sur le sujet « Attractiveness, Stochastic order »

Auteur : Grafiati

Publié le 9 mars 2023

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Articles de revues sur le sujet "Attractiveness, Stochastic order"

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Borrello, Davide. "Stochastic Order and Attractiveness for Particle Systems with Multiple Births, Deaths and Jumps." Electronic Journal of Probability 16 (2011): 106–51. http://dx.doi.org/10.1214/ejp.v16-852.

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Chen, Cheng, Canzhe Zhao, and Shuai Li. "Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 6202–10. http://dx.doi.org/10.1609/aaai.v36i6.20569.

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Online learning to rank (OLTR) interactively learns to choose lists of items from a large collection based on certain click models that describe users' click behaviors. Most recent works for this problem focus on the stochastic environment where the item attractiveness is assumed to be invariant during the learning process. In many real-world scenarios, however, the environment could be dynamic or even arbitrarily changing. This work studies the OLTR problem in both stochastic and adversarial environments under the position-based model (PBM). We propose a method based on the follow-the-regular

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Ota, Kaiichiro, Ikkyu Aihara, and Toshio Aoyagi. "Interaction mechanisms quantified from dynamical features of frog choruses." Royal Society Open Science 7, no. 3 (2020): 191693. http://dx.doi.org/10.1098/rsos.191693.

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We employ a mathematical model (a phase oscillator model) to describe the deterministic and stochastic features of frog choruses in which male frogs attempt to avoid call overlaps. The mathematical model with a general interaction term is identified using a Bayesian approach, and it qualitatively reproduces the stationary and dynamical features of the empirical data. In addition, we quantify the magnitude of attention paid among the male frogs from the identified model, and then analyse the relationship between attention and behavioural parameters using a statistical approach. Our analysis dem

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Vasin, Yu G. "Digital Simulation of Counterfeit Combating: Opportunities and Prospects." Intellectual property law 2 (July 1, 2021): 33–35. http://dx.doi.org/10.18572/2072-4322-2021-2-33-35.

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Countering counterfeit products protects the health of consumers, improves the quality of life and the competitiveness of the national economy. The turnover of counterfeit products entails a decrease in customs and tax payments, the attractiveness of investments in production and sectors of the economy, interferes with the observance of quality standards, and the construction of an innovative technological economy. Digital techniques expand the possibilities of understanding the trends of the phenomenon under consideration, which is applicable when constructing planning documents. Mathematical

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Andrianov, Andrey A., Ilya S. Kuptsov, Tatyana A. Osipova, Olga N. Andrianova, and Tatyana V. Utyanskaya. "Optimization models of a two-component nuclear energy system with thermal and fast reactors in a closed nuclear fuel cycle." Nuclear Energy and Technology 5, no. 1 (2019): 39–45. http://dx.doi.org/10.3897/nucet.5.33981.

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The article presents a description and some illustrative results of the application of two optimization models for a two-component nuclear energy system consisting of thermal and fast reactors in a closed nuclear fuel cycle. These models correspond to two possible options of developing Russian nuclear energy system, which are discussed in the expert community: (1) thermal and fast reactors utilizing uranium and mixed oxide fuel, (2) thermal reactors utilizing uranium oxide fuel and fast reactors utilizing mixed nitride uranium-plutonium fuel. The optimization models elaborated using the IAEA M

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Thèses sur le sujet "Attractiveness, Stochastic order"

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Borrello, Davide. "Interacting particle systems : stochastic order, attractiveness and random walk on small world grahs." Rouen, 2009. http://www.theses.fr/2009ROUES032.

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Le sujet principal de la thèse sont les systèmes de particules en interaction, qui sont des classes de processus spatio-temporels. Ces systèmes décrivent l'évolution de particules en interaction les unes avec les autres sur un espace discret fini ou infini. Dans la partie I, nous examinons l'ordre stochastique dans un système de particules avec multiples naissances, morts et sauts sur l'espace d-dimensionnel à coordonnées entières. Nous donnons des applications pour des modèles biologiques de diffusion d'épidémies et de systèmes de dynamiques de métapopulations. Dans la partie II, nous analyso

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BORRELLO, DAVIDE. "Interacting particle systems: stochastic order, attractiveness and random walks on small world graphs." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2009. http://hdl.handle.net/10281/7467.

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The main subject of the thesis is concerned with interacting particle systems, which are classes of spatio-temporal stochastic processes describing the evolution of particles in interaction with each other. The particles move on a finite or infinite discrete space and on each element of this space the state of the configuration is integer valued. Configurations of particles evolve in continuous time according to a Markov process. Here the space is either the infinite deterministic d-dimensional lattice or a random graph given by the finite d-dimensional torus with random matchings. In Part

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Actes de conférences sur le sujet "Attractiveness, Stochastic order"

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Barros, E. G. D., S. P. Szklarz, N. Khoshnevis Gargar, et al. "Field Development Optimization with Stochastic Gradient Method: Application to a Multi-Reservoir Carbonate Field in the Middle East." In SPE Reservoir Characterisation and Simulation Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212620-ms.

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Abstract Field development planning activities involve decisions that entail multi-billion-dollar investments. Making right design choices is crucial to the techno-economic success of the project. In this paper we demonstrate how state-of-the-art numerical model-based optimization techniques can support asset teams in this complex decision-making process. Optimization of real-life field development cases can be computationally very demanding due to the cost of running large amounts of large-scale reservoir simulations, the large number of variables to be optimized and the necessity of accounti

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