Výsledky vyhledávání - approximate statistical (dynamic OR dynamika) programming algorithm*

Simulation Analysis for UAV Search Algorithm Design Using Approximate Dynamic Programming

Autoři: Flint, Matthew Fernandez, Emmanuel Kelton, W. David

Zdroj: Military Operations Research, 2009 Jan 01. 14(2), 41-50.

Přístupová URL adresa: https://www.jstor.org/stable/43941127

Maximizing Net Present Value for Resource Constraint Project Scheduling Problems with Payments at Event Occurrences Using Approximate Dynamic Programming

Autoři: Tshewang Phuntsho Tad Gonsalves

Zdroj: Algorithms, Vol 17, Iss 5, p 180 (2024)

Témata: approximate dynamic programming, net present value, discounted cash flows, Discrete Cuckoo Search, Estimation of Distribution Algorithm, Ant Colony Optimization, Industrial engineering. Management engineering, T55.4-60.8, Electronic computers. Computer science, QA75.5-76.95

Relation: https://www.mdpi.com/1999-4893/17/5/180; https://doaj.org/toc/1999-4893; https://doaj.org/article/f1f51b9a3fe846d5a9c6f6a57971f0c7

Dostupnost: https://doi.org/10.3390/a17050180
https://doaj.org/article/f1f51b9a3fe846d5a9c6f6a57971f0c7

Energy-Efficient Transmission Strategy for Delay Tolerable Services in NOMA-Based Downlink With Two Users

Autoři: Mengmeng Bai Rui Zhu Jianxin Guo a další

Zdroj: IEEE Access, Vol 11, Pp 113227-113243 (2023)

Témata: Energy efficiency, delay tolerable, deep deterministic policy gradient, approximate statistical dynamic programming algorithm, proximal policy optimization, Electrical engineering. Electronics. Nuclear engineering, 7. Clean energy, TK1-9971

Přístupová URL adresa: https://doaj.org/article/1b13aa4558a749f69de123006e39486f

Energy-efficient power control strategy of the delay tolerable service based on the reinforcement learning.

Autoři: Bai, Mengmeng Zhu, Rui Guo, Jianxin a další

Zdroj: Computer Communications. Oct2023, Vol. 210, p102-115. 14p.

Témata: *DYNAMIC programming, *ENERGY consumption, DEEP reinforcement learning, GREEDY algorithms, REINFORCEMENT learning, POWER transmission

A fully adaptive framework for continuous-state stochastic dynamic programming.

Autoři: Fan, Huiyuan Tarun, Prashant K. Viswanatha, Amith a další

Zdroj: Computers & Operations Research. Nov2025, Vol. 183, pN.PAG-N.PAG. 1p.

Témata: *DYNAMIC programming, *STATISTICS, STATISTICAL models, SPACE exploration, COMPUTER engineering

Approximate dynamic programming methods in Bayesian preference elicitation.

Autoři: Fisher, William Zhang, Qiong Song, Yongjia

Zdroj: Quality Engineering. 2025, Vol. 37 Issue 3, p475-492. 18p.

Témata: *DECISION making, *QUESTIONNAIRES, *UTILITY functions, *SIMULATION methods & models, *BAYESIAN analysis, GREEDY algorithms, EXPERIMENTAL design

Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations.

Autoři: Hinz, Juri Tarnopolskaya, Tanya Yee, Jeremy

Zdroj: Annals of Operations Research. Mar2020, Vol. 286 Issue 1/2, p583-615. 33p.

Témata: *DYNAMIC programming, *STATISTICAL decision making, *ALGORITHMS, *MARKOV processes, NATURAL resources

Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming.

Autoři: Finnah, Benedikt Gönsch, Jochen Ziel, Florian

Zdroj: European Journal of Operational Research. Sep2022, Vol. 301 Issue 2, p726-746. 21p.

Témata: *DYNAMIC programming, *STATISTICAL decision making, *NUCLEAR power plants, *ELECTRICITY pricing, *MARKET prices, *BATTERY storage plants, ENERGY storage

Geografický termín: GERMANY

Inpatient Overflow: An Approximate Dynamic Programming Approach.

Autoři: Dai, J. G. Shi, Pengyi

Zdroj: Manufacturing & Service Operations Management (M&SOM). Fall2019, Vol. 21 Issue 4, p894-911. 18p.

Témata: *DYNAMIC programming, *STATISTICAL decision making, *DECISION making, FLUID control, CO-sleeping

The dynamic programming algorithm for management of real-time aircraft assignments

Autoři: Korotkova, Yu L Mezentsev, Yu A

Zdroj: Journal of Physics: Conference Series ; volume 1333, issue 3, page 032040 ; ISSN 1742-6588 1742-6596

Dostupnost: https://doi.org/10.1088/1742-6596/1333/3/032040
https://iopscience.iop.org/article/10.1088/1742-6596/1333/3/032040/pdf
https://iopscience.iop.org/article/10.1088/1742-6596/1333/3/032040

时延可容忍业务中的高能效信息传输策略研究. (Chinese)

Alternate Title: Research on energy-efficient information transmission strategy based on latency-tolerant services. (English)

Autoři: 邬伶凤 朱锐 曹九霄 a další

Zdroj: Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) / Chongqing Youdian Daxue Xuebao (Ziran Kexue Ban); Jun2025, Vol. 37 Issue 3, p333-345, 13p

Témata: DEEP reinforcement learning, REINFORCEMENT learning, GREEDY algorithms, POWER transmission, POWER resources

Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations

Autoři: Hinz, J Tarnopolskaya, T Yee, J

Témata: 01 Mathematical Sciences, 08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, Journal Article

URL: http://hdl.handle.net/10453/142926
http://purl.org/au-research/grants/arc/DP130103315
Annals of Operations Research
10.1007/s10479-018-2910-3
http://purl.org/au-research/grants/arc/DP130103315

Integrated intelligent neuro-evolutionary computing approach to study SEIRC model representing campylobacteriosis transmission dynamics

Autoři: Muhammad Shoaib Saba Kainat Areej Abdullah Alabduljabbar a další

Zdroj: Applied Mathematics in Science and Engineering, Vol 33, Iss 1 (2025)

Témata: Campylobacteriosis transmission, artificial neural networks, log-sigmoid, genetic algorithm, sequential quadratic programming, 34A34, Mathematics, QA1-939, Engineering (General). Civil engineering (General), TA1-2040

Relation: https://doaj.org/toc/2769-0911; https://doaj.org/article/a09fabef352f4655a0fb99db548b354a

Dostupnost: https://doi.org/10.1080/27690911.2024.2441257
https://doaj.org/article/a09fabef352f4655a0fb99db548b354a

On the use of transport and optimal control methods for Monte Carlo simulation

Autoři: Heng, Jeremy Doucet, Arnaud

Přispěvatelé: Heng, Jeremy Doucet, Arnaud

Témata: 519.5, Transport theory--Statistical methods, Optimal control, Normalizing constants, Sequential Monte Carlo, Approximate dynamic programming, Monte Carlo, Mass transport, Annealed importance sampling, Reinforcement learning, Markov chain Monte Carlo

Přístupová URL adresa: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740797

Deep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis

Autoři: Huré, Côme Pham, Huyên Bachouch, Achref a další

Přispěvatelé: Huré, Côme Pham, Huyên Bachouch, Achref a další

Zdroj: ISSN: 0036-1429 ; SIAM Journal on Numerical Analysis ; https://hal.science/hal-01949213 ; SIAM Journal on Numerical Analysis, 2021, 59 (1), pp.525-557. ⟨10.1137/20M1316640⟩.

Témata: performance iteration, quantization, Deep learning, dynamic programming, regress now, convergence analysis, statistical risk AMS subject classifications. 65C05, 90C39, 93E35, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/1812.04300; ARXIV: 1812.04300

Dostupnost: https://hal.science/hal-01949213
https://hal.science/hal-01949213v2/document
https://hal.science/hal-01949213v2/file/deepconsto_sinum_final.pdf
https://doi.org/10.1137/20M1316640

Integrated Scheduling of Stacker and Reclaimer in Dry Bulk Terminals: A Hybrid Genetic Algorithm.

Autoři: Torbi, Imane Belassiria, Imad Mazouzi, Mohamed a další

Zdroj: Computation; Mar2025, Vol. 13 Issue 3, p74, 35p

Témata: LINEAR programming, MATHEMATICAL optimization, PRODUCTION scheduling, MATHEMATICAL models, COMPUTATIONAL complexity, TABU search algorithm

Advanced Linearization Methods for Efficient and Accurate Compositional Reservoir Simulations.

Autoři: Asif, Ali Abd, Abdul Salam Abushaikha, Ahmad

Zdroj: Computation; Aug2025, Vol. 13 Issue 8, p191, 24p

Témata: MULTIPHASE flow, NONLINEAR equations, PARALLEL programming, LINEAR statistical models, CARBON dioxide injection, FLOW simulations, PETROLEUM production, COMPARATIVE studies

A Differentiable Approximation of the Graph Edit Distance ; Une approximation différentiable de la distance d'édition.

Autoři: Wallnig, Julia Brun, Luc Gaüzère, Benoit a další

Přispěvatelé: Wallnig, Julia Brun, Luc Gaüzère, Benoit a další

Zdroj: LNCS ; Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition S+SSPR ; https://normandie-univ.hal.science/hal-04740015 ; Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition S+SSPR, Andrea Torsello; Luca Rossi; Filippo Bergamasco; Luca Cosmo, Sep 2024, Venise (IT), Italy ; https://sites.google.com/view/s-sspr-2024

Témata: Graph Edit Distance Sinkhorn Algorithm Differentiable Solver, Graph Edit Distance, Sinkhorn Algorithm, Differentiable Solver, JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling, JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic Analysis, [INFO]Computer Science [cs], [MATH]Mathematics [math]

Geografické téma: Venise (IT), Italy

Dostupnost: https://normandie-univ.hal.science/hal-04740015
https://normandie-univ.hal.science/hal-04740015v1/document
https://normandie-univ.hal.science/hal-04740015v1/file/Evaluation_of_a_Continuous_Approximation_of_GED.pdf

Dynamic Frequent Subgraph Mining Algorithms Over Evolving Graphs: a Survey

Autoři: Abuzayed, Nourhan Bostanoglu, Belgin Ergenc

Témata: Exact frequent subgraph mining, Frequent subgraph mining, Approximate frequent subgraph mining, Evolving graph, Dynamic graph, Incremental subgraph mining

Relation: Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı; https://hdl.handle.net/11147/15025; 10; WOS:001334382700006; Q2; Q1

Dostupnost: https://hdl.handle.net/11147/15025
https://doi.org/10.7717/peerj-cs.2361

Optimistic Planning by Regularized Dynamic Programming

Autoři: Moulin, Antoine Neu, Gergely

Témata: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2302.14004