Artículos de revistas sobre el tema "Surrogate Function"
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THIEL, MARCO, M. CARMEN ROMANO, UDO SCHWARZ, JÜRGEN KURTHS y JENS TIMMER. "SURROGATE-BASED HYPOTHESIS TEST WITHOUT SURROGATES". International Journal of Bifurcation and Chaos 14, n.º 06 (junio de 2004): 2107–14. http://dx.doi.org/10.1142/s0218127404010527.
Texto completoZiff, Elizabeth. "“Honey, I Want to Be a Surrogate”: How Military Spouses Negotiate and Navigate Surrogacy With Their Service Member Husbands". Journal of Family Issues 40, n.º 18 (18 de julio de 2019): 2774–800. http://dx.doi.org/10.1177/0192513x19862843.
Texto completoAmbarwati, Mega Dewi y Ghina Azmita Kamila. "THE EVALUATION OF SURROGACY’S LEGAL SYSTEM IN INDONESIA AS COMPARISON TO INDIA’S LEGISLATION". Diponegoro Law Review 4, n.º 2 (1 de octubre de 2019): 167. http://dx.doi.org/10.14710/dilrev.4.2.2019.167-180.
Texto completoTenne, Yoel. "An Analysis of the RBF Hyperparameter Impact on Surrogate-Assisted Evolutionary Optimization". Scientific Programming 2022 (20 de diciembre de 2022): 1–12. http://dx.doi.org/10.1155/2022/5175941.
Texto completoLiu, Bolin y Liyang Xie. "Reliability Analysis of Structures by Iterative Improved Ensemble of Surrogate Method". Shock and Vibration 2019 (24 de octubre de 2019): 1–13. http://dx.doi.org/10.1155/2019/6357104.
Texto completoZeng, Wei, Xian Chao Wang y Ying Sheng Wang. "Surrogating for High Dimensional Computationally Expensive Multi-Modal Functions with Elliptical Basis Function Models". Applied Mechanics and Materials 733 (febrero de 2015): 880–84. http://dx.doi.org/10.4028/www.scientific.net/amm.733.880.
Texto completoIuliano, Emiliano. "Efficient Design Optimization Assisted by Sequential Surrogate Models". International Journal of Aerospace Engineering 2019 (12 de mayo de 2019): 1–34. http://dx.doi.org/10.1155/2019/4937261.
Texto completoMalmquist, Anna y Sonja Höjerström. "Constructions of surrogates, egg donors, and mothers: Swedish gay fathers’ narratives". Feminism & Psychology 30, n.º 4 (14 de mayo de 2020): 508–28. http://dx.doi.org/10.1177/0959353520922415.
Texto completo&NA;. "Is endothelial function a useful surrogate?" Inpharma Weekly &NA;, n.º 1256 (septiembre de 2000): 2. http://dx.doi.org/10.2165/00128413-200012560-00002.
Texto completoChodos, Alan y Eric Myers. "Testing the surrogate zeta-function method". Canadian Journal of Physics 64, n.º 5 (1 de mayo de 1986): 633–36. http://dx.doi.org/10.1139/p86-117.
Texto completoBemporad, Alberto. "Global optimization via inverse distance weighting and radial basis functions". Computational Optimization and Applications 77, n.º 2 (27 de julio de 2020): 571–95. http://dx.doi.org/10.1007/s10589-020-00215-w.
Texto completoCunningham, Thomas V., Leslie P. Scheunemann, Robert M. Arnold y Douglas White. "How do clinicians prepare family members for the role of surrogate decision-maker?" Journal of Medical Ethics 44, n.º 1 (17 de julio de 2017): 21–26. http://dx.doi.org/10.1136/medethics-2016-103808.
Texto completoPan, Jeng-Shyang, Li-Gang Zhang, Shu-Chuan Chu, Chin-Shiuh Shieh y Junzo Watada. "Surrogate-Assisted Hybrid Meta-Heuristic Algorithm with an Add-Point Strategy for a Wireless Sensor Network". Entropy 25, n.º 2 (9 de febrero de 2023): 317. http://dx.doi.org/10.3390/e25020317.
Texto completoYounis, Adel y Zuomin Dong. "High-Fidelity Surrogate Based Multi-Objective Optimization Algorithm". Algorithms 15, n.º 8 (7 de agosto de 2022): 279. http://dx.doi.org/10.3390/a15080279.
Texto completoDushatskiy, Arkadiy, Tanja Alderliesten y Peter A. N. Bosman. "A Novel Approach to Designing Surrogate-assisted Genetic Algorithms by Combining Efficient Learning of Walsh Coefficients and Dependencies". ACM Transactions on Evolutionary Learning and Optimization 1, n.º 2 (23 de julio de 2021): 1–23. http://dx.doi.org/10.1145/3453141.
Texto completoHavinga, Jos, Gerrit Klaseboer y A. H. van den Boogaard. "Sequential Optimization of Strip Bending Process Using Multiquadric Radial Basis Function Surrogate Models". Key Engineering Materials 554-557 (junio de 2013): 911–18. http://dx.doi.org/10.4028/www.scientific.net/kem.554-557.911.
Texto completoLu, Dan y Daniel Ricciuto. "Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques". Geoscientific Model Development 12, n.º 5 (6 de mayo de 2019): 1791–807. http://dx.doi.org/10.5194/gmd-12-1791-2019.
Texto completoSolomon, Michael R. "The Missing Link: Surrogate Consumers in the Marketing Chain". Journal of Marketing 50, n.º 4 (octubre de 1986): 208–18. http://dx.doi.org/10.1177/002224298605000406.
Texto completoOuyang, Qi, Xiao Qian Chen y Wen Yao. "Comparison of the Function Regression Method and Data Classification Method for Limit State Function Approximation". Advanced Materials Research 774-776 (septiembre de 2013): 1738–44. http://dx.doi.org/10.4028/www.scientific.net/amr.774-776.1738.
Texto completoChen, Guodong, Kai Zhang, Liming Zhang, Xiaoming Xue, Dezhuang Ji, Chuanjin Yao, Jun Yao y Yongfei Yang. "Global and Local Surrogate-Model-Assisted Differential Evolution for Waterflooding Production Optimization". SPE Journal 25, n.º 01 (9 de diciembre de 2019): 105–18. http://dx.doi.org/10.2118/199357-pa.
Texto completoBadhurshah, Rameez y Abdus Samad. "Surrogate Assisted Design Optimization of an Air Turbine". International Journal of Rotating Machinery 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/563483.
Texto completoBerkemeier, Manuel y Sebastian Peitz. "Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models". Mathematical and Computational Applications 26, n.º 2 (15 de abril de 2021): 31. http://dx.doi.org/10.3390/mca26020031.
Texto completoClaywell, Brian C., Vu Dinh, Mathieu Fourment, Connor O. McCoy y Frederick A. Matsen IV. "A Surrogate Function for One-Dimensional Phylogenetic Likelihoods". Molecular Biology and Evolution 35, n.º 1 (26 de septiembre de 2017): 242–46. http://dx.doi.org/10.1093/molbev/msx253.
Texto completoFrick, Matthias y Franz Weidinger. "Endothelial Function: A Surrogate Endpoint in Cardiovascular Studies?" Current Pharmaceutical Design 13, n.º 17 (1 de junio de 2007): 1741–50. http://dx.doi.org/10.2174/138161207780831211.
Texto completoKeane, Andy J. y Ivan I. Voutchkov. "Robust design optimization using surrogate models". Journal of Computational Design and Engineering 7, n.º 1 (1 de febrero de 2020): 44–55. http://dx.doi.org/10.1093/jcde/qwaa005.
Texto completoYi, Jin, Yichi Shen y Christine A. Shoemaker. "A multi-fidelity RBF surrogate-based optimization framework for computationally expensive multi-modal problems with application to capacity planning of manufacturing systems". Structural and Multidisciplinary Optimization 62, n.º 4 (17 de mayo de 2020): 1787–807. http://dx.doi.org/10.1007/s00158-020-02575-7.
Texto completoMonakov, A. A. "A Versatile Algorithm for Autofocusing SAR Images". Journal of the Russian Universities. Radioelectronics 24, n.º 1 (26 de febrero de 2021): 22–33. http://dx.doi.org/10.32603/1993-8985-2021-24-1-22-33.
Texto completoKunakote, Tawatchai y Sujin Bureerat. "Surrogate-Assisted Multiobjective Evolutionary Algorithms for Structural Shape and Sizing Optimisation". Mathematical Problems in Engineering 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/695172.
Texto completoMai, Hau T., Jaewook Lee, Joowon Kang, H. Nguyen-Xuan y Jaehong Lee. "An Improved Blind Kriging Surrogate Model for Design Optimization Problems". Mathematics 10, n.º 16 (12 de agosto de 2022): 2906. http://dx.doi.org/10.3390/math10162906.
Texto completoZenke, Friedemann y Tim P. Vogels. "The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks". Neural Computation 33, n.º 4 (2021): 899–925. http://dx.doi.org/10.1162/neco_a_01367.
Texto completoZeng, Wei, Yue Yang, Huan Xie y Lin-jun Tong. "CF-Kriging surrogate model based on the combination forecasting method". Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 230, n.º 18 (9 de agosto de 2016): 3274–84. http://dx.doi.org/10.1177/0954406215610149.
Texto completoBajer, Lukáš, Zbyněk Pitra, Jakub Repický y Martin Holeňa. "Gaussian Process Surrogate Models for the CMA Evolution Strategy". Evolutionary Computation 27, n.º 4 (diciembre de 2019): 665–97. http://dx.doi.org/10.1162/evco_a_00244.
Texto completoHengel, Richard L. y Joseph A. Kovacs. "Surrogate Markers of Immune Function in Human Immunodeficiency Virus–Infected Patients: What Are They Surrogates For?" Journal of Infectious Diseases 188, n.º 12 (15 de diciembre de 2003): 1791–93. http://dx.doi.org/10.1086/379901.
Texto completoChechile, Richard A. "Using Hazard and Surrogate Functions for Understanding Memory and Forgetting". AppliedMath 2, n.º 4 (4 de octubre de 2022): 518–46. http://dx.doi.org/10.3390/appliedmath2040031.
Texto completoOzol, Cengiz. "The Surrogate Wage Function and Capital: Theory with Measurement". Canadian Journal of Economics 24, n.º 1 (febrero de 1991): 175. http://dx.doi.org/10.2307/135485.
Texto completoSUGAI, Tomotaka, Kohei SHINTANI, Atsuji ABE y Yasushi YAMAMOTO. "Surrogate modeling of transfer function using feature extraction method". Proceedings of Design & Systems Conference 2019.29 (2019): 2110. http://dx.doi.org/10.1299/jsmedsd.2019.29.2110.
Texto completoPacheco, Jorge E., Cristina H. Amon y Susan Finger. "Bayesian Surrogates Applied to Conceptual Stages of the Engineering Design Process". Journal of Mechanical Design 125, n.º 4 (1 de diciembre de 2003): 664–72. http://dx.doi.org/10.1115/1.1631580.
Texto completoJenkins, William F. y Peter Gerstoft. "Acquisition functions in Bayesian optimization of ocean acoustic waveguides using Gaussian processes". Journal of the Acoustical Society of America 151, n.º 4 (abril de 2022): A267. http://dx.doi.org/10.1121/10.0011293.
Texto completoKaridis, J. P. y S. R. Turns. "Efficient Optimization of Computationally Expensive Objective Functions". Journal of Mechanisms, Transmissions, and Automation in Design 108, n.º 3 (1 de septiembre de 1986): 336–39. http://dx.doi.org/10.1115/1.3258736.
Texto completoLu, Li, Yizhong Wu, Qi Zhang y Ping Qiao. "A Transformation-Based Improved Kriging Method for the Black Box Problem in Reliability-Based Design Optimization". Mathematics 11, n.º 1 (1 de enero de 2023): 218. http://dx.doi.org/10.3390/math11010218.
Texto completoEggert, R. J. y R. W. Mayne. "Probabilistic Optimal Design Using Successive Surrogate Probability Density Functions". Journal of Mechanical Design 115, n.º 3 (1 de septiembre de 1993): 385–91. http://dx.doi.org/10.1115/1.2919203.
Texto completoJenkins, William F. y Peter Gerstoft. "Applications of Bayesian optimization with a Gaussian process surrogate model in ocean acoustics". Journal of the Acoustical Society of America 152, n.º 4 (octubre de 2022): A157. http://dx.doi.org/10.1121/10.0015876.
Texto completoOthman, Norazila y Masahiro Kanazaki. "Development of Digital Flight Motion Methodology Based on Aerodynamic Derivatives Approximation". Journal of Robotics and Mechatronics 28, n.º 2 (19 de abril de 2016): 215–25. http://dx.doi.org/10.20965/jrm.2016.p0215.
Texto completoZhao, Mengjie, Kai Zhang, Guodong Chen, Xinggang Zhao, Jun Yao, Chuanjin Yao, Liming Zhang y Yongfei Yang. "A Classification-Based Surrogate-Assisted Multiobjective Evolutionary Algorithm for Production Optimization under Geological Uncertainty". SPE Journal 25, n.º 05 (18 de junio de 2020): 2450–69. http://dx.doi.org/10.2118/201229-pa.
Texto completoShafie Khorassani, Fatema, Jeremy M. G. Taylor, Niko Kaciroti y Michael R. Elliott. "Incorporating Covariates into Measures of Surrogate Paradox Risk". Stats 6, n.º 1 (17 de febrero de 2023): 322–44. http://dx.doi.org/10.3390/stats6010020.
Texto completoSwingler, Kevin. "Learning and Searching Pseudo-Boolean Surrogate Functions from Small Samples". Evolutionary Computation 28, n.º 2 (junio de 2020): 317–38. http://dx.doi.org/10.1162/evco_a_00257.
Texto completoProtonotarios, Nicholas E., George A. Kastis, Andreas D. Fotopoulos, Andreas G. Tzakos, Dimitrios Vlachos y Nikolaos Dikaios. "Motion-Compensated PET Image Reconstruction via Separable Parabolic Surrogates". Mathematics 11, n.º 1 (23 de diciembre de 2022): 55. http://dx.doi.org/10.3390/math11010055.
Texto completoCandida Fratazzi y Jixiao Niu. "Accelerated orphan drug approval: surrogate endpoints". World Journal of Advanced Pharmaceutical and Medical Research 2, n.º 1 (30 de enero de 2022): 001–7. http://dx.doi.org/10.53346/wjapmr.2022.2.1.0021.
Texto completoKamali, M., K. Ponnambalam y E. D. Soulis. "Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization". Hydrology and Earth System Sciences Discussions 4, n.º 4 (23 de julio de 2007): 2307–21. http://dx.doi.org/10.5194/hessd-4-2307-2007.
Texto completoNa, Chongzheng y Huixin Liu. "A Historical Experience Surrogate Model Assisted Particle Swarm Optimization for Expensive Black-box Problems". Highlights in Science, Engineering and Technology 7 (3 de agosto de 2022): 83–88. http://dx.doi.org/10.54097/hset.v7i.1021.
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