Results 31 to 40 of about 561,088 (291)

Sensitivity analysis and optimization method of partition surrogate model based on physical knowledge driven

Hangkong gongcheng jinzhan
The problem of "dimensionality disaster" of design variable is a key technical problem that restricts the application of current agent-based optimization algorithms.
SHAO Mengying, XIA Lu, ZHANG Wei, ZHAO Ke   +3 more
doaj   +1 more source

Research on an Accuracy Optimization Algorithm of Kriging Model Based on a Multipoint Filling Criterion

Mathematics, 2022
The optimization method based on the surrogate model has been widely used in the simulation and calculation process of complex engineering models. However, in this process, the low accuracy and computational efficiency of the surrogate model has always ...
Shande Li, Shuai Yuan, Shaowei Liu, Jian Wen, Qibai Huang   +4 more
doaj   +1 more source

Clinical Insights Into Hypercalcemia of Malignancy in Childhood

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Hypercalcemia of malignancy (HCM) is a rare but life‐threatening metabolic emergency in children that occurs in less than 1% of pediatric cancer cases, with a reported incidence ranging from 0.4% to 1.0% across different studies. While it is observed in 10%–20% of adult malignancies, pediatric HCM remains relatively uncommon.
Hüseyin Anıl Korkmaz
wiley   +1 more source

Research on Surrogate Model of Dam Structural Behavior for Multi‐Output Problem

Engineering Reports
The establishment efficiency of the surrogate model is often affected by the multi‐output problem during the establishment process. It is an urgent issue to solve how to establish a multi‐output joint surrogate model more quickly while ensuring a certain
Yuan Qiao, Liang Jiaming, Li Zhanchao, Ebrahim Yahya Khailah   +3 more
doaj   +1 more source

Dynamic Analysis of a Moored Spar Platform in a Uniform Current: Fluid Load Prediction Using a Surrogate Model

Journal of Marine Science and Engineering
A moored spar platform, equipped with various instruments, serves as a crucial tool in hydrological monitoring. However, conducting dynamic analyses of a single spar that endures wind and current requires significant amount of computational time.
Xinming Wei, Xiangqian Zhu, Ruiyang Cao, Jinglei Wang, Xinyu Li, Qing’an Li, Jin-Hwan Choi   +6 more
doaj   +1 more source

Surrogate modeling based cognitive decision engine for optimization of WLAN performance [PDF]

, 2017
Due to the rapid growth of wireless networks and the dearth of the electromagnetic spectrum, more interference is imposed to the wireless terminals which constrains their performance. In order to mitigate such performance degradation, this paper proposes
Chemmangat, Krishnan, Deschrijver, Dirk, Dhaene, Tom, Hoebeke, Jeroen, Mehari, Michael, Moerman, Ingrid, Pakparvar, Mostafa, Plets, David, Tanghe, Emmeric, Ulaganathan, Selvakumar   +9 more
core   +1 more source

Pediatric Oncology Nursing Competencies in Latin America and the Caribbean: A Scoping Review to Inform Practice, Education, and Research

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Nurses are central to cancer care for children and adolescents, yet no comprehensive synthesis has defined essential core competencies for pediatric oncology nursing (PON) practice internationally, particularly in Latin America and the Caribbean (LAC).
Luís Carlos Lopes‐Júnior, Edmara Bazoni Soares Maia, Soad Fuentes‐Alabí, Courtney E. Sullivan, Monnie Abraham, Mauricio Maza, Liliana Vásquez Ponce, Regina Aparecida Garcia Lima   +7 more
wiley   +1 more source

Modify Leave-One-Out Cross Validation by Moving Validation Samples around Random Normal Distributions: Move-One-Away Cross Validation

Applied Sciences, 2020
The leave-one-out cross validation (LOO-CV), which is a model-independent evaluate method, cannot always select the best of several models when the sample size is small.
Liye Lv, Xueguan Song, Wei Sun
doaj   +1 more source

A Joint Optimization Algorithm Based on the Optimal Shape Parameter–Gaussian Radial Basis Function Surrogate Model and Its Application

Mathematics, 2023
We propose a joint optimization algorithm that combines the optimal shape parameter–Gaussian radial basis function (G-RBF) surrogate model with global and local optimization techniques to improve accuracy and reduce costs.
Jian Sun, Ling Wang, Dianxuan Gong
doaj   +1 more source

KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization [PDF]

, 2013
This paper investigates the control of an ML component within the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) devoted to black-box optimization.
Loshchilov, Ilya, Schoenauer, Marc, Sebag, Michèle   +2 more
core   +3 more sources