Artículos de revistas sobre el tema "Sequential Monte Carlo (SMC) method"
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Wang, Liangliang, Shijia Wang y Alexandre Bouchard-Côté. "An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics". Systematic Biology 69, n.º 1 (6 de junio de 2019): 155–83. http://dx.doi.org/10.1093/sysbio/syz028.
Texto completoFinke, Axel, Arnaud Doucet y Adam M. Johansen. "Limit theorems for sequential MCMC methods". Advances in Applied Probability 52, n.º 2 (junio de 2020): 377–403. http://dx.doi.org/10.1017/apr.2020.9.
Texto completoCong-An, Xu, Xu Congqi, Dong Yunlong, Xiong Wei, Chai Yong y Li Tianmei. "A Novel Sequential Monte Carlo-Probability Hypothesis Density Filter for Particle Impoverishment Problem". Journal of Computational and Theoretical Nanoscience 13, n.º 10 (1 de octubre de 2016): 6872–77. http://dx.doi.org/10.1166/jctn.2016.5640.
Texto completoAbu Znaid, Ammar M. A., Mohd Yamani Idna Idris, Ainuddin Wahid Abdul Wahab, Liana Khamis Qabajeh y Omar Adil Mahdi. "Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review". Journal of Sensors 2017 (2017): 1–19. http://dx.doi.org/10.1155/2017/1430145.
Texto completoDeng, Yue, Yongzhen Pei, Changguo Li y Bin Zhu. "Model Selection and Parameter Estimation for an Improved Approximate Bayesian Computation Sequential Monte Carlo Algorithm". Discrete Dynamics in Nature and Society 2022 (30 de junio de 2022): 1–14. http://dx.doi.org/10.1155/2022/8969903.
Texto completoHsu, Kuo-Lin. "Hydrologic forecasting using artificial neural networks: a Bayesian sequential Monte Carlo approach". Journal of Hydroinformatics 13, n.º 1 (2 de abril de 2010): 25–35. http://dx.doi.org/10.2166/hydro.2010.044.
Texto completoWeng, Zhipeng, Jinghua Zhou y Zhengdong Zhan. "Reliability Evaluation of Standalone Microgrid Based on Sequential Monte Carlo Simulation Method". Energies 15, n.º 18 (14 de septiembre de 2022): 6706. http://dx.doi.org/10.3390/en15186706.
Texto completoRöder, Lenard L., Patrick Dewald, Clara M. Nussbaumer, Jan Schuladen, John N. Crowley, Jos Lelieveld y Horst Fischer. "Data quality enhancement for field experiments in atmospheric chemistry via sequential Monte Carlo filters". Atmospheric Measurement Techniques 16, n.º 5 (7 de marzo de 2023): 1167–78. http://dx.doi.org/10.5194/amt-16-1167-2023.
Texto completoNakano, S., K. Suzuki, K. Kawamura, F. Parrenin y T. Higuchi. "A sequential Bayesian approach for the estimation of the age–depth relationship of Dome Fuji ice core". Nonlinear Processes in Geophysics Discussions 2, n.º 3 (26 de junio de 2015): 939–68. http://dx.doi.org/10.5194/npgd-2-939-2015.
Texto completoRusyda Roslan, Nur Nabihah, NoorFatin Farhanie Mohd Fauzi y Mohd Ikhwan Muhammad Ridzuan. "Variance reduction technique in reliability evaluation for distribution system by using sequential Monte Carlo simulation". Bulletin of Electrical Engineering and Informatics 11, n.º 6 (1 de diciembre de 2022): 3061–68. http://dx.doi.org/10.11591/eei.v11i6.3950.
Texto completoGU, FENG y XIAOLIN HU. "ANALYSIS AND QUANTIFICATION OF DATA ASSIMILATION BASED ON SEQUENTIAL MONTE CARLO METHODS FOR WILDFIRE SPREAD SIMULATION". International Journal of Modeling, Simulation, and Scientific Computing 01, n.º 04 (diciembre de 2010): 445–68. http://dx.doi.org/10.1142/s1793962310000298.
Texto completoRusyda Roslan, Nur Nabihah, NoorFatin Farhanie Mohd Fauzi y Mohd Ikhwan Muhammad Ridzuan. "Monte Carlo simulation convergences’ percentage and position in future reliability evaluation". International Journal of Electrical and Computer Engineering (IJECE) 12, n.º 6 (1 de diciembre de 2022): 6218. http://dx.doi.org/10.11591/ijece.v12i6.pp6218-6227.
Texto completoNakano, Shin'ya, Kazue Suzuki, Kenji Kawamura, Frédéric Parrenin y Tomoyuki Higuchi. "A sequential Bayesian approach for the estimation of the age–depth relationship of the Dome Fuji ice core". Nonlinear Processes in Geophysics 23, n.º 1 (29 de febrero de 2016): 31–44. http://dx.doi.org/10.5194/npg-23-31-2016.
Texto completoToni, Tina, David Welch, Natalja Strelkowa, Andreas Ipsen y Michael P. H. Stumpf. "Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems". Journal of The Royal Society Interface 6, n.º 31 (9 de julio de 2008): 187–202. http://dx.doi.org/10.1098/rsif.2008.0172.
Texto completoCameron, Scott, Hans Eggers y Steve Kroon. "A Sequential Marginal Likelihood Approximation Using Stochastic Gradients". Proceedings 33, n.º 1 (3 de diciembre de 2019): 18. http://dx.doi.org/10.3390/proceedings2019033018.
Texto completoLiu, Qinming y Ming Dong. "Online Health Management for Complex Nonlinear Systems Based on Hidden Semi-Markov Model Using Sequential Monte Carlo Methods". Mathematical Problems in Engineering 2012 (2012): 1–22. http://dx.doi.org/10.1155/2012/951584.
Texto completoNoh, S. J., Y. Tachikawa, M. Shiiba y S. Kim. "Applying sequential Monte Carlo methods into a distributed hydrologic model: lagged particle filtering approach with regularization". Hydrology and Earth System Sciences Discussions 8, n.º 2 (4 de abril de 2011): 3383–420. http://dx.doi.org/10.5194/hessd-8-3383-2011.
Texto completoImani, Mahdi, Seyede Fatemeh Ghoreishi, Douglas Allaire y Ulisses M. Braga-Neto. "MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 7858–65. http://dx.doi.org/10.1609/aaai.v33i01.33017858.
Texto completoInfante, Saba, Luis Sánchez, Aracelis Hernández y José Marcano. "Sequential Monte Carlo Filters with Parameters Learning for Commodity Pricing Models". Statistics, Optimization & Information Computing 9, n.º 3 (22 de junio de 2021): 694–716. http://dx.doi.org/10.19139/soic-2310-5070-814.
Texto completoShafii, Mahyar, Bryan Tolson y L. Shawn Matott. "Improving the efficiency of Monte Carlo Bayesian calibration of hydrologic models via model pre-emption". Journal of Hydroinformatics 17, n.º 5 (23 de febrero de 2015): 763–70. http://dx.doi.org/10.2166/hydro.2015.043.
Texto completoZhan, Ronghui, Liping Wang y Jun Zhang. "Joint Tracking and Classification of Multiple Targets with Scattering Center Model and CBMeMBer Filter". Sensors 20, n.º 6 (17 de marzo de 2020): 1679. http://dx.doi.org/10.3390/s20061679.
Texto completoOgundijo, Oyetunji E. y Xiaodong Wang. "Characterization of tumor heterogeneity by latent haplotypes: a sequential Monte Carlo approach". PeerJ 6 (30 de mayo de 2018): e4838. http://dx.doi.org/10.7717/peerj.4838.
Texto completoYuan, Xianghui, Feng Lian y Chongzhao Han. "Multiple-Model Cardinality Balanced Multitarget Multi-Bernoulli Filter for Tracking Maneuvering Targets". Journal of Applied Mathematics 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/727430.
Texto completoSamuelsson, Oscar, Anders Björk, Jesús Zambrano y Bengt Carlsson. "Gaussian process regression for monitoring and fault detection of wastewater treatment processes". Water Science and Technology 75, n.º 12 (25 de marzo de 2017): 2952–63. http://dx.doi.org/10.2166/wst.2017.162.
Texto completoNoh, S. J., Y. Tachikawa, M. Shiiba y S. Kim. "Applying sequential Monte Carlo methods into a distributed hydrologic model: lagged particle filtering approach with regularization". Hydrology and Earth System Sciences 15, n.º 10 (25 de octubre de 2011): 3237–51. http://dx.doi.org/10.5194/hess-15-3237-2011.
Texto completoZhang, Jungen. "Bearings-only multitarget tracking based onRao-Blackwellized particle CPHD filter". International Journal of Circuits, Systems and Signal Processing 14 (13 de enero de 2021): 1129–36. http://dx.doi.org/10.46300/9106.2020.14.141.
Texto completoIkoma, Norikazu, Ryuichi Yamaguchi, Hideaki Kawano y Hiroshi Maeda. "Tracking of Multiple Moving Objects in Dynamic Image of Omni-Directional Camera Using PHD Filter". Journal of Advanced Computational Intelligence and Intelligent Informatics 12, n.º 1 (20 de enero de 2008): 16–25. http://dx.doi.org/10.20965/jaciii.2008.p0016.
Texto completoOlivieri, D., J. Faro, I. Gomez-Conde y C. E. Tadokoro. "Tracking T and B cells from two-photon microscopy imaging using constrained SMC clusters". Journal of Integrative Bioinformatics 8, n.º 3 (1 de diciembre de 2011): 141–57. http://dx.doi.org/10.1515/jib-2011-180.
Texto completoDrovandi, C. C., N. Cusimano, S. Psaltis, B. A. J. Lawson, A. N. Pettitt, P. Burrage y K. Burrage. "Sampling methods for exploring between-subject variability in cardiac electrophysiology experiments". Journal of The Royal Society Interface 13, n.º 121 (agosto de 2016): 20160214. http://dx.doi.org/10.1098/rsif.2016.0214.
Texto completoKim, Sun Young, Chang Ho Kang y Chan Gook Park. "SMC-CPHD Filter with Adaptive Survival Probability for Multiple Frequency Tracking". Applied Sciences 12, n.º 3 (27 de enero de 2022): 1369. http://dx.doi.org/10.3390/app12031369.
Texto completoAlahmadi, Amani A., Jennifer A. Flegg, Davis G. Cochrane, Christopher C. Drovandi y Jonathan M. Keith. "A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models". Royal Society Open Science 7, n.º 3 (marzo de 2020): 191315. http://dx.doi.org/10.1098/rsos.191315.
Texto completoMartínez-Barberá, Humberto, Pablo Bernal-Polo y David Herrero-Pérez. "Sensor Modeling for Underwater Localization Using a Particle Filter". Sensors 21, n.º 4 (23 de febrero de 2021): 1549. http://dx.doi.org/10.3390/s21041549.
Texto completoRuchi, Sangeetika, Svetlana Dubinkina y Jana de Wiljes. "Fast hybrid tempered ensemble transform filter formulation for Bayesian elliptical problems via Sinkhorn approximation". Nonlinear Processes in Geophysics 28, n.º 1 (15 de enero de 2021): 23–41. http://dx.doi.org/10.5194/npg-28-23-2021.
Texto completoZeng, HongCheng, Jie Chen, PengBo Wang, Wei Liu, XinKai Zhou y Wei Yang. "Moving Target Detection in Multi-Static GNSS-Based Passive Radar Based on Multi-Bernoulli Filter". Remote Sensing 12, n.º 21 (24 de octubre de 2020): 3495. http://dx.doi.org/10.3390/rs12213495.
Texto completoZhang, Xiaoguo, Yujin Kuang, Haoran Yang, Hang Lu y Yuan Yang. "UWB Indoor Localization Algorithm Using Firefly of Multistage Optimization on Particle Filter". Journal of Sensors 2021 (15 de diciembre de 2021): 1–9. http://dx.doi.org/10.1155/2021/1383767.
Texto completoJ., Kiruba y Rajesh T. "Enabling accurate range free localization for mo-bile sensor networks". International Journal of Engineering & Technology 7, n.º 1.3 (31 de diciembre de 2017): 1. http://dx.doi.org/10.14419/ijet.v7i1.3.8975.
Texto completoWang, Shuqiang, Yanyan Shen, Changhong Shi, Tao Wang, Zhiming Wei y Hanxiong Li. "Defining Biological Networks for Noise Buffering and Signaling Sensitivity Using Approximate Bayesian Computation". Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/625754.
Texto completoSun, Ming y Chao Shi. "Application of Particle Filtering in Visual Tracking". Advanced Materials Research 485 (febrero de 2012): 207–12. http://dx.doi.org/10.4028/www.scientific.net/amr.485.207.
Texto completoRoldán-Blay, Carlos, Carlos Roldán-Porta, Eduardo Quiles y Guillermo Escrivá-Escrivá. "Smart Cooperative Energy Supply Strategy to Increase Reliability in Residential Stand-Alone Photovoltaic Systems". Applied Sciences 11, n.º 24 (10 de diciembre de 2021): 11723. http://dx.doi.org/10.3390/app112411723.
Texto completoChen, Zhikun, Bin’an Wang, Ruiheng Yang y Yuchao Lou. "Joint Direction of Arrival-Polarization Parameter Tracking Algorithm Based on Multi-Target Multi-Bernoulli Filter". Remote Sensing 15, n.º 16 (8 de agosto de 2023): 3929. http://dx.doi.org/10.3390/rs15163929.
Texto completoWang, Xilu y Yaochu Jin. "Knowledge Transfer Based on Particle Filters for Multi-Objective Optimization". Mathematical and Computational Applications 28, n.º 1 (18 de enero de 2023): 14. http://dx.doi.org/10.3390/mca28010014.
Texto completoThorn, Graeme J. y John R. King. "The metabolic network of Clostridium acetobutylicum: Comparison of the approximate Bayesian computation via sequential Monte Carlo (ABC-SMC) and profile likelihood estimation (PLE) methods for determinability analysis". Mathematical Biosciences 271 (enero de 2016): 62–79. http://dx.doi.org/10.1016/j.mbs.2015.10.016.
Texto completoLin, Ye y Sean B. Andersson. "Expectation maximization based framework for joint localization and parameter estimation in single particle tracking from segmented images". PLOS ONE 16, n.º 5 (21 de mayo de 2021): e0243115. http://dx.doi.org/10.1371/journal.pone.0243115.
Texto completoSchaaf, Alexander, Miguel de la Varga, Florian Wellmann y Clare E. Bond. "Constraining stochastic 3-D structural geological models with topology information using approximate Bayesian computation in GemPy 2.1". Geoscientific Model Development 14, n.º 6 (28 de junio de 2021): 3899–913. http://dx.doi.org/10.5194/gmd-14-3899-2021.
Texto completoAvecilla, Grace, Julie N. Chuong, Fangfei Li, Gavin Sherlock, David Gresham y Yoav Ram. "Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics". PLOS Biology 20, n.º 5 (27 de mayo de 2022): e3001633. http://dx.doi.org/10.1371/journal.pbio.3001633.
Texto completoBeskos, Alexandros, Dan O. Crisan, Ajay Jasra y Nick Whiteley. "Error Bounds and Normalising Constants for Sequential Monte Carlo Samplers in High Dimensions". Advances in Applied Probability 46, n.º 01 (marzo de 2014): 279–306. http://dx.doi.org/10.1017/s0001867800007047.
Texto completoBeskos, Alexandros, Dan O. Crisan, Ajay Jasra y Nick Whiteley. "Error Bounds and Normalising Constants for Sequential Monte Carlo Samplers in High Dimensions". Advances in Applied Probability 46, n.º 1 (marzo de 2014): 279–306. http://dx.doi.org/10.1239/aap/1396360114.
Texto completoChen, Shoudong, Yan-lin Sun y Yang Liu. "Forecast of stock price fluctuation based on the perspective of volume information in stock and exchange market". China Finance Review International 8, n.º 3 (20 de agosto de 2018): 297–314. http://dx.doi.org/10.1108/cfri-08-2017-0184.
Texto completoLian, Feng, Chen Li, Chongzhao Han y Hui Chen. "Convergence Analysis for the SMC-MeMBer and SMC-CBMeMBer Filters". Journal of Applied Mathematics 2012 (2012): 1–25. http://dx.doi.org/10.1155/2012/584140.
Texto completoAhmed, Imtiaz. "Dolphin Whistle Track Estimation Using Sequential Monte Carlo Probability Hypothesis Density Filter". Dhaka University Journal of Science 62, n.º 1 (7 de febrero de 2015): 17–20. http://dx.doi.org/10.3329/dujs.v62i1.21954.
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