Artículos de revistas sobre el tema "DYNAMIC MACHINE LEARNING METHODOLOGY"
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Barr, Joseph R., Eden A. Ellis, Antonio Kassab, Christian L. Redfearn, Narayanan Nani Srinivasan y Kurtis B. Voris. "Home Price Index: A Machine Learning Methodology". International Journal of Semantic Computing 11, n.º 01 (marzo de 2017): 111–33. http://dx.doi.org/10.1142/s1793351x17500015.
Texto completoPérez Moreno, F., V. F. Gómez Comendador, R. Delgado-Aguilera Jurado, M. Zamarreño Suárez, D. Janisch y R. M. Arnaldo Valdés. "Dynamic sector characterisation model with the application of machine learning techniques". IOP Conference Series: Materials Science and Engineering 1226, n.º 1 (1 de febrero de 2022): 012018. http://dx.doi.org/10.1088/1757-899x/1226/1/012018.
Texto completoNavarro, Osvaldo, Jones Yudi, Javier Hoffmann, Hector Gerardo Muñoz Hernandez y Michael Hübner. "A Machine Learning Methodology for Cache Memory Design Based on Dynamic Instructions". ACM Transactions on Embedded Computing Systems 19, n.º 2 (17 de marzo de 2020): 1–20. http://dx.doi.org/10.1145/3376920.
Texto completoPRIORE, PAOLO, DAVID DE LA FUENTE, ALBERTO GOMEZ y JAVIER PUENTE. "DYNAMIC SCHEDULING OF MANUFACTURING SYSTEMS WITH MACHINE LEARNING". International Journal of Foundations of Computer Science 12, n.º 06 (diciembre de 2001): 751–62. http://dx.doi.org/10.1142/s0129054101000849.
Texto completoIskhakov, Fedor, John Rust y Bertel Schjerning. "Machine learning and structural econometrics: contrasts and synergies". Econometrics Journal 23, n.º 3 (29 de agosto de 2020): S81—S124. http://dx.doi.org/10.1093/ectj/utaa019.
Texto completoKo, Jeong Hoon. "Machining Stability Categorization and Prediction Using Process Model Guided Machine Learning". Metals 12, n.º 2 (9 de febrero de 2022): 298. http://dx.doi.org/10.3390/met12020298.
Texto completoGarcía Plaza, Eustaquio, Pedro Jose Núñez López, Angel Ramon Martín y E. Beamud. "Virtual Machining Applied to the Teaching of Manufacturing Technology". Materials Science Forum 692 (julio de 2011): 120–27. http://dx.doi.org/10.4028/www.scientific.net/msf.692.120.
Texto completoHewawasam, Hasitha, Gayan Kahandawa y Yousef Ibrahim. "Machine Learning-Based Agoraphilic Navigation Algorithm for Use in Dynamic Environments with a Moving Goal". Machines 11, n.º 5 (28 de abril de 2023): 513. http://dx.doi.org/10.3390/machines11050513.
Texto completoLu, M., L. Groeneveld, D. Karssenberg, S. Ji, R. Jentink, E. Paree y E. Addink. "GEOMORPHOLOGICAL MAPPING OF INTERTIDAL AREAS". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (28 de junio de 2021): 75–80. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-75-2021.
Texto completoCarputo, Francesco, Danilo D’Andrea, Giacomo Risitano, Aleksandr Sakhnevych, Dario Santonocito y Flavio Farroni. "A Neural-Network-Based Methodology for the Evaluation of the Center of Gravity of a Motorcycle Rider". Vehicles 3, n.º 3 (15 de julio de 2021): 377–89. http://dx.doi.org/10.3390/vehicles3030023.
Texto completoKarpov, Platon I., Chengkun Huang, Iskandar Sitdikov, Chris L. Fryer, Stan Woosley y Ghanshyam Pilania. "Physics-informed Machine Learning for Modeling Turbulence in Supernovae". Astrophysical Journal 940, n.º 1 (1 de noviembre de 2022): 26. http://dx.doi.org/10.3847/1538-4357/ac88cc.
Texto completoLiang, S. Y. y S. A. Perry. "In-Process Compensation for Milling Cutter Runout via Chip Load Manipulation". Journal of Engineering for Industry 116, n.º 2 (1 de mayo de 1994): 153–60. http://dx.doi.org/10.1115/1.2901925.
Texto completoSujatha, Dr P., Bora Mounika, Dukka Raju, Gokavarapu Rahul y Mulli Gangaraju. "Ad Demand Forecasting Prediction using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 4 (30 de abril de 2023): 4771–94. http://dx.doi.org/10.22214/ijraset.2023.51330.
Texto completoRizzo, Valentino, Stefano Traverso y Marco Mellia. "Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning". Proceedings on Privacy Enhancing Technologies 2021, n.º 1 (1 de enero de 2021): 43–63. http://dx.doi.org/10.2478/popets-2021-0004.
Texto completoLeventides, John, Evangelos Melas, Costas Poulios y Paraskevi Boufounou. "Analysis of chaotic economic models through Koopman operators, EDMD, Takens' theorem and Machine Learning". Data Science in Finance and Economics 2, n.º 4 (2022): 416–36. http://dx.doi.org/10.3934/dsfe.2022021.
Texto completoKoo, Jamin, Kyucheol Choi, Peter Lee, Amanda Polley, Raghavendra Sumanth Pudupakam, Josephine Tsang, Elmer Fernandez et al. "Predicting Dynamic Clinical Outcomes of the Chemotherapy for Canine Lymphoma Patients Using a Machine Learning Model". Veterinary Sciences 8, n.º 12 (2 de diciembre de 2021): 301. http://dx.doi.org/10.3390/vetsci8120301.
Texto completoRozos, Evangelos. "Machine Learning, Urban Water Resources Management and Operating Policy". Resources 8, n.º 4 (14 de noviembre de 2019): 173. http://dx.doi.org/10.3390/resources8040173.
Texto completoGolmohammadi, Amir-Mohammad, Hasan Rasay, Zaynab Akhoundpour Amiri, Maryam Solgi y Negar Balajeh. "Soft Computing Methodology to Optimize the Integrated Dynamic Models of Cellular Manufacturing Systems in a Robust Environment". Mathematical Problems in Engineering 2021 (11 de noviembre de 2021): 1–13. http://dx.doi.org/10.1155/2021/3040391.
Texto completoElngar, Ahmed y Adriana Burlea-Schiopoiu. "Feature Selection and Dynamic Network Traffic Congestion Classification based on Machine Learning for Internet of Things". Wasit Journal of Computer and Mathematics Science 2, n.º 2 (1 de julio de 2023): 76–91. http://dx.doi.org/10.31185/wjcms.150.
Texto completoNarang, Akhil, Victor Mor-Avi, Aldo Prado, Valentina Volpato, David Prater, Gloria Tamborini, Laura Fusini et al. "Machine learning based automated dynamic quantification of left heart chamber volumes". European Heart Journal - Cardiovascular Imaging 20, n.º 5 (9 de octubre de 2018): 541–49. http://dx.doi.org/10.1093/ehjci/jey137.
Texto completoPiltan, Farzin, Alexander E. Prosvirin, Inkyu Jeong, Kichang Im y Jong-Myon Kim. "Rolling-Element Bearing Fault Diagnosis Using Advanced Machine Learning-Based Observer". Applied Sciences 9, n.º 24 (10 de diciembre de 2019): 5404. http://dx.doi.org/10.3390/app9245404.
Texto completoSilva-Aravena, Fabián y Jenny Morales. "Dynamic Surgical Waiting List Methodology: A Networking Approach". Mathematics 10, n.º 13 (1 de julio de 2022): 2307. http://dx.doi.org/10.3390/math10132307.
Texto completoPuissant, Agathe, Roy El Hourany, Anastase Alexandre Charantonis, Chris Bowler y Sylvie Thiria. "Inversion of Phytoplankton Pigment Vertical Profiles from Satellite Data Using Machine Learning". Remote Sensing 13, n.º 8 (8 de abril de 2021): 1445. http://dx.doi.org/10.3390/rs13081445.
Texto completoSzostak, Daniel y Krzysztof Walkowiak. "Application of Machine Learning Algorithms for Traffic Forecasting in Dynamic Optical Networks with Service Function Chains". Foundations of Computing and Decision Sciences 45, n.º 3 (1 de septiembre de 2020): 217–32. http://dx.doi.org/10.2478/fcds-2020-0012.
Texto completoAnand, Dr C., N. Vasuki, S. Nirmala, N. Naveen y S. Prabakaran. "Greedy Dynamic Blocking for Rumour Detection on Live Twitter Using Machine Learning". Revista Gestão Inovação e Tecnologias 11, n.º 2 (5 de junio de 2021): 364–73. http://dx.doi.org/10.47059/revistageintec.v11i2.1673.
Texto completoPresti, Claudia, Federica De Santis y Francesca Bernini. "Value co-creation via machine learning from a configuration theory perspective". European Journal of Innovation Management 26, n.º 7 (3 de agosto de 2023): 449–77. http://dx.doi.org/10.1108/ejim-01-2023-0104.
Texto completoGultekin, Muaz y Oya Kalipsiz. "Story Point-Based Effort Estimation Model with Machine Learning Techniques". International Journal of Software Engineering and Knowledge Engineering 30, n.º 01 (enero de 2020): 43–66. http://dx.doi.org/10.1142/s0218194020500035.
Texto completoLiu, Tao, Dongqi Li, Jianjun Chen, Yanbing Chen, Tao Yang y Jianhua Cao. "Active Learning on Dynamic Clustering for Drift Compensation in an Electronic Nose System". Sensors 19, n.º 16 (19 de agosto de 2019): 3601. http://dx.doi.org/10.3390/s19163601.
Texto completoSun, Jin, Zhengyu Chen y Fu Wang. "A Novel ML-Aided Methodology for SINS/GPS Integrated Navigation Systems during GPS Outages". Remote Sensing 14, n.º 23 (23 de noviembre de 2022): 5932. http://dx.doi.org/10.3390/rs14235932.
Texto completoNovikov, I. S., Y. V. Suleimanov y A. V. Shapeev. "Automated calculation of thermal rate coefficients using ring polymer molecular dynamics and machine-learning interatomic potentials with active learning". Physical Chemistry Chemical Physics 20, n.º 46 (2018): 29503–12. http://dx.doi.org/10.1039/c8cp06037a.
Texto completoSani, Shehu, Hanbing Xia, Jelena Milisavljevic-Syed y Konstantinos Salonitis. "Supply Chain 4.0: A Machine Learning-Based Bayesian-Optimized LightGBM Model for Predicting Supply Chain Risk". Machines 11, n.º 9 (4 de septiembre de 2023): 888. http://dx.doi.org/10.3390/machines11090888.
Texto completoAn, Qing, Ruoli Tang, Hongfeng Su, Jun Zhang y Xin Li. "Robust configuration and intelligent MPPT control for building integrated photovoltaic system based on extreme learning machine". Journal of Intelligent & Fuzzy Systems 40, n.º 6 (21 de junio de 2021): 12283–300. http://dx.doi.org/10.3233/jifs-210424.
Texto completoPatiño, José, Ángel Encalada-Dávila, José Sampietro, Christian Tutivén, Carlos Saldarriaga y Imin Kao. "Damping Ratio Prediction for Redundant Cartesian Impedance-Controlled Robots Using Machine Learning Techniques". Mathematics 11, n.º 4 (17 de febrero de 2023): 1021. http://dx.doi.org/10.3390/math11041021.
Texto completoShin, Hyun-Jun, Kyoung-Woo Cho y Chang-Heon Oh. "SVM-Based Dynamic Reconfiguration CPS for Manufacturing System in Industry 4.0". Wireless Communications and Mobile Computing 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/5795037.
Texto completoKim, Hyun Il y Kun Yeun Han. "Linking Hydraulic Modeling with a Machine Learning Approach for Extreme Flood Prediction and Response". Atmosphere 11, n.º 9 (15 de septiembre de 2020): 987. http://dx.doi.org/10.3390/atmos11090987.
Texto completoNeff, P., D. Steineder, B. Stummer y T. Clemens. "Estimation of Initial Hydrocarbon Saturation Applying Machine Learning Under Petrophysical Uncertainty". SPE Reservoir Evaluation & Engineering 24, n.º 02 (4 de marzo de 2021): 325–40. http://dx.doi.org/10.2118/203384-pa.
Texto completoKhessam, Medjdoub, Abdelkader Lousdad, Abdeldjebar Hazzab, Miloud Rezkallah y Ambrish Chandra. "A new application for fast prediction and protection of electrical drive wheel speed using machine learning methodology". Indonesian Journal of Electrical Engineering and Computer Science 26, n.º 3 (1 de junio de 2022): 1290. http://dx.doi.org/10.11591/ijeecs.v26.i3.pp1290-1298.
Texto completoKuzmin, A. G., Y. A. Titiov y A. Y. Zaitceva. "MASS SPECTROMETRIC DIAGNOSIS OF RECOVERY AFTER RESPIRATORY ILLNESS USING MACHINE LEARNING METHODS". BIOTECHNOLOGY: STATE OF THE ART AND PERSPECTIVES 1, n.º 2022-20 (2022): 74–77. http://dx.doi.org/10.37747/2312-640x-2022-20-74-77.
Texto completoLokanan, Mark, Vincent Tran y Nam Hoai Vuong. "Detecting anomalies in financial statements using machine learning algorithm". Asian Journal of Accounting Research 4, n.º 2 (14 de octubre de 2019): 181–201. http://dx.doi.org/10.1108/ajar-09-2018-0032.
Texto completoAlhussan, Amel Ali, Abdelaziz A. Abdelhamid, S. K. Towfek, Abdelhameed Ibrahim, Marwa M. Eid, Doaa Sami Khafaga y Mohamed S. Saraya. "Classification of Diabetes Using Feature Selection and Hybrid Al-Biruni Earth Radius and Dipper Throated Optimization". Diagnostics 13, n.º 12 (12 de junio de 2023): 2038. http://dx.doi.org/10.3390/diagnostics13122038.
Texto completoShaheen, Memoona, Mehreen Arshad y Owais Iqbal. "Role and Key Applications of Artificial Intelligence & Machine Learning in Transportation". European Journal of Technology 4, n.º 1 (31 de diciembre de 2020): 47–59. http://dx.doi.org/10.47672/ejt.632.
Texto completoChitturi, Sathya R., Nicolas G. Burdet, Youssef Nashed, Daniel Ratner, Aashwin Mishra, T. J. Lane, Matthew Seaberg et al. "A machine learning photon detection algorithm for coherent x-ray ultrafast fluctuation analysis". Structural Dynamics 9, n.º 5 (septiembre de 2022): 054302. http://dx.doi.org/10.1063/4.0000161.
Texto completoVaienti, Beatrice, Rémi Petitpierre, Isabella di Lenardo y Frédéric Kaplan. "Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction". Remote Sensing 15, n.º 13 (30 de junio de 2023): 3352. http://dx.doi.org/10.3390/rs15133352.
Texto completoLegendre, Cesar, Vincent Ficat-Andrieu, Athanasios Poulos, Yuya Kitano, Yoshitaka Nakashima, Wataru Kobayashi y Gaku Minorikawa. "A machine learning-based methodology for computational aeroacoustics predictions of multi-propeller drones". INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, n.º 3 (1 de agosto de 2021): 3467–78. http://dx.doi.org/10.3397/in-2021-2415.
Texto completoGino, Vinícius L. S., Rogério G. Negri, Felipe N. Souza, Erivaldo A. Silva, Adriano Bressane, Tatiana S. G. Mendes y Wallace Casaca. "Integrating Unsupervised Machine Intelligence and Anomaly Detection for Spatio-Temporal Dynamic Mapping Using Remote Sensing Image Series". Sustainability 15, n.º 6 (7 de marzo de 2023): 4725. http://dx.doi.org/10.3390/su15064725.
Texto completoSantos, Marcone Ferreira, Alessandro Corrêa Victorino y Hugo Pousseur. "Model-based and machine learning-based high-level controller for autonomous vehicle navigation: lane centering and obstacles avoidance". IAES International Journal of Robotics and Automation (IJRA) 12, n.º 1 (1 de marzo de 2023): 84. http://dx.doi.org/10.11591/ijra.v12i1.pp84-97.
Texto completoPrajapati, Keyur y Dinesh J Prajapati. "Web Auto Configuration for N-Tier in VM based Dynamic Environment by Reinforcement Learning Approach: A Study". Computer Science & Engineering: An International Journal 12, n.º 1 (28 de febrero de 2022): 25–34. http://dx.doi.org/10.5121/cseij.2022.12104.
Texto completoPomponio, Laura, Marc Le Goc, Alain Anfosso y Eric Pascual. "Levels of Abstraction for Behavior Modeling in the GerHome Project". International Journal of E-Health and Medical Communications 3, n.º 3 (julio de 2012): 12–28. http://dx.doi.org/10.4018/jehmc.2012070102.
Texto completoDadras Javan, Farzad, Italo Aldo Campodonico Avendano, Behzad Najafi, Amin Moazami y Fabio Rinaldi. "Machine-Learning-Based Prediction of HVAC-Driven Load Flexibility in Warehouses". Energies 16, n.º 14 (16 de julio de 2023): 5407. http://dx.doi.org/10.3390/en16145407.
Texto completoHabib, Ahed y Umut Yildirim. "Estimating mechanical and dynamic properties of rubberized concrete using machine learning techniques: a comprehensive study". Engineering Computations 39, n.º 8 (19 de agosto de 2022): 3129–78. http://dx.doi.org/10.1108/ec-09-2021-0527.
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