Academic literature on the topic 'Discrete descent'
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Journal articles on the topic "Discrete descent"
Sobral, Manuela. "Descent for Discrete (Co)fibrations." Applied Categorical Structures 12, no. 5/6 (October 2004): 527–35. http://dx.doi.org/10.1023/b:apcs.0000049316.87223.a4.
Full textCASTRO, CARLOS, FRANCISCO PALACIOS, and ENRIQUE ZUAZUA. "AN ALTERNATING DESCENT METHOD FOR THE OPTIMAL CONTROL OF THE INVISCID BURGERS EQUATION IN THE PRESENCE OF SHOCKS." Mathematical Models and Methods in Applied Sciences 18, no. 03 (March 2008): 369–416. http://dx.doi.org/10.1142/s0218202508002723.
Full textCarlson, David, Ya-Ping Hsieh, Edo Collins, Lawrence Carin, and Volkan Cevher. "Stochastic Spectral Descent for Discrete Graphical Models." IEEE Journal of Selected Topics in Signal Processing 10, no. 2 (March 2016): 296–311. http://dx.doi.org/10.1109/jstsp.2015.2505684.
Full textDiaz-Lopez, Alexander, Pamela E. Harris, Erik Insko, Mohamed Omar, and Bruce E. Sagan. "Descent polynomials." Discrete Mathematics 342, no. 6 (June 2019): 1674–86. http://dx.doi.org/10.1016/j.disc.2019.01.034.
Full textDAIDZIC, Nihad E. "An algebraic model of high-altitude aircraft decompression and emergency descent." Aviation 21, no. 3 (August 3, 2018): 92–101. http://dx.doi.org/10.3846/16487788.2017.1380081.
Full textEhrenborg, Richard, and Swapneel Mahajan. "Maximizing the descent statistic." Annals of Combinatorics 2, no. 2 (June 1998): 111–29. http://dx.doi.org/10.1007/bf01608482.
Full textMahavier, W. T. "A convergence result for discreet steepest decent in weighted sobolev spaces." Abstract and Applied Analysis 2, no. 1-2 (1997): 67–72. http://dx.doi.org/10.1155/s1085337597000274.
Full textNg, Chi-Kong, Duan Li, and Lian-Sheng Zhang. "Discrete global descent method for discrete global optimization and nonlinear integer programming." Journal of Global Optimization 37, no. 3 (August 17, 2006): 357–79. http://dx.doi.org/10.1007/s10898-006-9053-9.
Full textMurota, Kazuo. "On Steepest Descent Algorithms for Discrete Convex Functions." SIAM Journal on Optimization 14, no. 3 (January 2004): 699–707. http://dx.doi.org/10.1137/s1052623402419005.
Full textYang, Yong-jian, and Lian-sheng Zhang. "A gradually descent method for discrete global optimization." Journal of Shanghai University (English Edition) 11, no. 1 (February 2007): 39–44. http://dx.doi.org/10.1007/s11741-007-0106-1.
Full textDissertations / Theses on the topic "Discrete descent"
Olsen, McCabe J. "HILBERT BASES, DESCENT STATISTICS, AND COMBINATORIAL SEMIGROUP ALGEBRAS." UKnowledge, 2018. https://uknowledge.uky.edu/math_etds/52.
Full textHapp, Alexander Thomas. "A Combinatorial Miscellany: Antipodes, Parking Cars, and Descent Set Powers." UKnowledge, 2018. https://uknowledge.uky.edu/math_etds/53.
Full textBoberg, Jonas. "Counting Double-Descents and Double-Inversions in Permutations." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54431.
Full textDjaneye-Boundjou, Ouboti Seydou Eyanaa. "Discrete-time Concurrent Learning for System Identification and Applications: Leveraging Memory Usage for Good Learning." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton151298579862899.
Full textCoelho, Francisco Carlos Rodrigues. "Alocação de geração distribuída em sistemas de distribuição de energia elétrica via metaheurística empírica discreta." Universidade Federal de Juiz de Fora (UFJF), 2018. https://repositorio.ufjf.br/jspui/handle/ufjf/6506.
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A alocação de Geração Distribuída (GD) em sistemas de distribuição de energia elétrica consiste em determinar os barramentos para conexão destas unidades geradoras, e o montante de potência a ser injetado, visando um ou mais objetivos, que podem ser: redução das perdas de potência ativa, melhorias no perfil de tensão, minimização dos custos operacionais, maximização da geração de energia, ganhos ambientais, dentre outros. O principal objetivo considerado neste trabalho é a minimização das perdas de potência ativa, mantendo as tensões dos barramentos dentro de limites recomendados. Para alcançar este objetivo, uma metodologia de otimização é proposta, tratando separadamente os problemas de localização das unidades geradoras no sistema, e o dimensionamento destas unidades. A determinação das barras com conexão de GD é realizada através de uma nova técnica de otimização metaheurística, implementada no MATLAB, denominada Metaheurística Empírica Discreta (MED). Já o dimensionamento das unidades de GD é realizado de duas formas distintas, a depender do tipo de sistema de distribuição analisado. No caso dos sistemas cujos dados são equivalentes monofásicos, o montante de potencia é determinado por um Fluxo de Potência Ótimo implementado no software comercial LINGO. A segunda estratégia de determinação da potência despachada é empregada no caso dos testes realizados com sistemas trifásicos desbalanceados, cujo dimensionamento é feito pelo método do gradiente descendente e o cálculo do fluxo de potência é realizado pelo software OpenDSS. Os três sistemas equivalentes monofásicos utilizados são compostos por 33, 69 e 476 barras, enquanto os dois trifásicos desequilibrados possuem 34 e 123 barras. A qualidade da metodologia proposta na resolução do problema de alocação de geração distribuída é avaliada através de comparações com a literatura especializada, comparações com outras metaheurísticas e testes de robustez. Os resultados provenientes de simulações com alocação de três e quatro unidades de GD em sistemas de distribuição de energia elétrica mostram que a metodologia proposta é eficiente, sendo capaz de produzir resultados com significativas reduções nas perdas de potência ativa e perfis de tensão adequados.
The optimal Distributed Generation (DG) allocation problem consists in choosing the best locations of those distributed power plants at the distribution system, and to define its amount of power injection. The approach can be either single or multiobjective. The main objectives are: minimization of total power loss, voltage profile improvement, operational cost minimization, maximization of distributed generation capacity, environmental gains, among others. In this work, the main goal pursued is the total power loss minimization of the distribution system, keeping the buses voltages within the predetermined limits. To achieve this goal, an optimization methodology is proposed. This approach treats separately the location problem and the power dispatched by the generation units. The busbars connected to distributed generation are determined through a new metaheuristic algorithm, implemented in MATLAB, named Empirical Discrete Metaheuristic (EDM). The amount of power injection is solved by an Optimum Power Flow implemented in the commercial software LINGO, or by the Steepest Descent Method in the MATLAB environment. The first strategy to determine the DG dispatch is used on simulations with single phase equivalents systems. The second one is employed in the amount of power determination in unbalanced three phase systems, which the power flow is carried out by the open source software OpenDSS. The three single phase equivalent test systems analyzed are composed by 33, 69 and 476 buses, while the two systems with three phases have 34 and 123 buses, each. To evaluate the proposed methodology quality, comparisons to published works in the specialized literature are made. Also, robustness tests and comparisons to other well succeed metaheuristics are carried out. The results were obtained from simulations with three and four DG units in electric power distribution systems. These results consistently show that the proposed methodology is efficient, providing DGs configurations that significantly reduces the active power losses and keep the voltages at adequate levels.
Коваленко, Владислав Вячеславович. "Дослідження режимів мереж 35/10кВ операторів системи розподілу електроенергії." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/39563.
Full textIn the bachelor's thesis on "Study of 35 / 10kV network modes of electricity distribution system operators" there are two parts: the first - calculation (section 1), which implements the general power problems of calculation and optimization of modes and short circuit currents for sufficiently complex electrical networks and the second - research (section 2), which is devoted to the analysis of the regimes of 35 / 10kV schemes of Odesaoblenergo. The object of studythere is an individual 110/35/10 kV substation, 110/35 kV supply and distribution networks, and typical problem-oriented experimental or industrial models. The subject of research there are unknown mode characteristics (voltages, losses, regulating values of reactive power, currents KZ, etc.), and also models of matrices of conductivity and resistance, methods of the decision of nonlinear electric equations and other. The goal of the work - to confirm the level of engineering qualification of the bachelor's degree and according to the individual task, to develop the calculation scheme of Odesaoblenergo and determine the main characteristics (voltage, power loss, electricity consumption) for the regime days of summer and winter maximum. The bachelor's thesis contains 67 pages, 29 drawings, 7 tables, 4 illustrations and 11 literary references. To implement the task, the educational computer complex L_APEZ, industrial power complexes RAOTV, Z_REGIM, OPTIM.QT are involved. In the process of realization of tasks individual calculation schemes are developed.
Palomares, Roberto P. "Optical flow: related problems." Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/403061.
Full textLa estimación del movimiento es una de las piezas clave para muchos de los problemas de procesamiento de imagen y visión artificial. Esta tesis aborda el problema de la estimación de campos de movimiento densos de una escena a través del Cálculo de Variaciones. En particular, realizamos contribuciones a los problemas de optical flow (flujo óptico) y scene flow (flujo de escena), as\'i como una aplicación donde se demuestra su importancia. El flujo óptico tiene como objetivo estimar el movimiento aparente causado por el movimiento relativo entre el observador y la escena. En la primera parte del manuscrito presentamos un nuevo regularizador para flujo óptico capaz de recuperar las rotaciones de los objetos manteniendo un comportamiento similar a la Variación Total en el resto de movimientos. A continuación describimos un modelo de `binary video inpainting' donde el método previo juega un papel fundamental completando las zonas ocluidas en las que el flujo es desconocido y estimando las trayectorias de los objetos visibles. En la segunda parte, presentamos una nueva estrategia de minimización para flujo óptico capaz de capturar largos desplazamientos independientemente del funcional de energía escogido. Dicha estrategia es un proceso de optimización en dos fases que a partir de un conjunto discreto de correspondencias obtiene un flujo denso posteriormente refinado en la segunda fase. Los experimentos realizados validan la contribución presentada ya que los flujos ópticos son siempre más precisos que los obtenidos con el esquema multi-escala al minimizar el mismo funcional de energía. La última parte de este documento se centra en el problema de scene flow, definido como el campo de movimiento 3D de una escena. En dicho aporte extendemos la estrategia de minimización previa para flujo óptico al contexto de secene flow. Además presentamos un modelo de energía desacoplado, basado en el propuesto por Wedel et al. (2011), que aprovecha las distintas vistas de la escena para describir explícitamente las oclusiones- obteniendo una mayor precisi\'on en las discontinuidades del campo de movimiento.
Books on the topic "Discrete descent"
Marti, Kurt. Computation of descent directions and stationary (efficient) points in stochastic optimization problems having discrete distributions. Neubiberg: Universität der Bundeswehr München, 1986.
Find full textDescent directions and efficient solutions in discretely distributed stochastic programs. Berlin: Springer-Verlag, 1988.
Find full textMarti, Kurt. Descent Directions and Efficient Solutions in Discretely Distributed Stochastic Programs. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-662-02558-1.
Full textAbbes, Ahmed, Michel Gros, and Takeshi Tsuji. Almost étale coverings. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691170282.003.0005.
Full textChancy, Myriam J. A. Autochthonomies. University of Illinois Press, 2020. http://dx.doi.org/10.5622/illinois/9780252043048.001.0001.
Full textMichel, Bierlaire. Optimization: Principles and Algorithms. EPFL Press, 2015. http://dx.doi.org/10.55430/6116v1mb.
Full textBook chapters on the topic "Discrete descent"
Brimberg, Jack, Nenad Mladenović, Raca Todosijević, and Dragan Urošević. "Variable Neighborhood Descent for the Capacitated Clustering Problem." In Discrete Optimization and Operations Research, 336–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44914-2_27.
Full textAfric, Petar, Adrian Satja Kurdija, Lucija Sikic, Marin Silic, Goran Delac, Klemo Vladimir, and Sinisa Srbljic. "Population-Based Variable Neighborhood Descent for Discrete Optimization." In Artificial Intelligence and Mobile Services – AIMS 2019, 1–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23367-9_1.
Full textBubeck, Sébastien, Michael B. Cohen, James R. Lee, and Yin Tat Lee. "Metrical task systems on trees via mirror descent and unfair gluing." In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 89–97. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2019. http://dx.doi.org/10.1137/1.9781611975482.6.
Full textCruttwell, Geoffrey S. H., Bruno Gavranović, Neil Ghani, Paul Wilson, and Fabio Zanasi. "Categorical Foundations of Gradient-Based Learning." In Programming Languages and Systems, 1–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99336-8_1.
Full textShantz, Michael, and Edlyn Teske. "Solving the Elliptic Curve Discrete Logarithm Problem Using Semaev Polynomials, Weil Descent and Gröbner Basis Methods – An Experimental Study." In Lecture Notes in Computer Science, 94–107. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42001-6_7.
Full textFrey, Gerhard, and Tanja Lange. "Background on Weil Descent." In Discrete Mathematics and Its Applications, 125–32. Chapman and Hall/CRC, 2005. http://dx.doi.org/10.1201/9781420034981.ch7.
Full textPallot, Judith, and Tat'yana Nefedova. "Ethno-cultural Differentiation in Household Production." In Russia's Unknown Agriculture. Oxford University Press, 2007. http://dx.doi.org/10.1093/oso/9780199227419.003.0013.
Full textRamsay-Jordan, Natasha N. "What Sports Do You Play? Actually, My Major Is Mathematics." In Women's Influence on Inclusion, Equity, and Diversity in STEM Fields, 66–75. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8870-2.ch003.
Full textConference papers on the topic "Discrete descent"
Farsa, Davood Zaman, and Shahryar Rahnamayan. "Discrete Coordinate Descent (DCD)." In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2020. http://dx.doi.org/10.1109/smc42975.2020.9283201.
Full textPochapsky, Eugene, and David Casasent. "Discrete Steepest Descent Algorithms And Their Realization On Optical Analog Processors." In 32nd Annual Technical Symposium, edited by J. P. Letellier. SPIE, 1989. http://dx.doi.org/10.1117/12.948555.
Full textLombardi, Giovanni, Francois Beux, and Mattia de? Michieli Vitturi. "Analysis of 2D Coupled Sails: Use of an Optimization Technique Based on Turbulent Viscous Flows." In SNAME 16th Chesapeake Sailing Yacht Symposium. SNAME, 2003. http://dx.doi.org/10.5957/csys-2003-010.
Full textGharavi, Hani, Xueqin Liu, and Sean McLoone. "Warm start oriented discrete coordinate descent for dynamic CVR: A UK case study." In 2017 28th Irish Signals and Systems Conference (ISSC). IEEE, 2017. http://dx.doi.org/10.1109/issc.2017.7983628.
Full textLiu, Liwei, and Maozhi Xu. "Improvements to the Descent Step in the Number Field Sieve for Discrete Logarithms." In 2020 International Conference on Computer, Information and Telecommunication Systems (CITS). IEEE, 2020. http://dx.doi.org/10.1109/cits49457.2020.9232505.
Full textHeinke, Simon, and Herbert Werner. "A Gradient Descent Method for Finite Horizon Distributed Control of Discrete Time Systems." In 2021 60th IEEE Conference on Decision and Control (CDC). IEEE, 2021. http://dx.doi.org/10.1109/cdc45484.2021.9683326.
Full textYang, Hong, Ling Chen, Minglong Lei, Lingfeng Niu, Chuan Zhou, and Peng Zhang. "Discrete Embedding for Latent Networks." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/170.
Full textLyubimov, Vladislav, and Ekaterina Kurkina. "Optimal Discrete Control Law for Rotation of a Descent Probe with a Small Inertial Asymmetry during the Descent in the Atmosphere of Mars." In 2019 XXI International Conference Complex Systems: Control and Modeling Problems (CSCMP). IEEE, 2019. http://dx.doi.org/10.1109/cscmp45713.2019.8976630.
Full textAlessandri, Angelo, and Mauro Gaggero. "Moving horizon state estimation for constrained discrete-time systems by using fast descent methods." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8263967.
Full textGuo, Guibing, Enneng Yang, Li Shen, Xiaochun Yang, and Xiaodong He. "Discrete Trust-aware Matrix Factorization for Fast Recommendation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/191.
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