Results 31 to 40 of about 5,249 (165)

Wart-Treatment Efficacy Prediction Using a CMA-ES-Based Dendritic Neuron Model

Applied Sciences, 2023
Warts are a prevalent condition worldwide, affecting approximately 10% of the global population. In this study, a machine learning method based on a dendritic neuron model is proposed for wart-treatment efficacy prediction.
Shuangbao Song, Botao Zhang, Xingqian Chen, Qiang Xu, Jia Qu   +4 more
doaj   +1 more source

Support Vector Regression-Based Optimization for Triple Friction Pendulum Bearings: Achieving Computational Efficiency [PDF]

Journal of Soft Computing in Civil Engineering
Triple friction pendulum bearings (TFPBs) enhance the seismic resilience of base-isolated buildings. However, optimizing TFPB designs is computationally expensive, necessitating surrogate modeling techniques.
Mahnaz Akbarzaghi, Behrooz Ahmadi Nedushan, Hamed Tajammolian   +2 more
doaj   +1 more source

Prenatal diagnosis by trio exome sequencing in fetuses with ultrasound anomalies: A powerful diagnostic tool

Frontiers in Genetics, 2023
Introduction: Prenatal ultrasound (US) anomalies are detected in around 5%–10% of pregnancies. In prenatal diagnosis, exome sequencing (ES) diagnostic yield ranges from 6% to 80% depending on the inclusion criteria.
Frédéric Tran Mau-Them, Frédéric Tran Mau-Them, Julian Delanne, Anne-Sophie Denommé-Pichon, Anne-Sophie Denommé-Pichon, Hana Safraou, Hana Safraou, Ange-Line Bruel, Ange-Line Bruel, Antonio Vitobello, Antonio Vitobello, Aurore Garde, Sophie Nambot, Nicolas Bourgon, Caroline Racine, Arthur Sorlin, Arthur Sorlin, Sébastien Moutton, Nathalie Marle, Thierry Rousseau, Paul Sagot, Emmanuel Simon, Catherine Vincent-Delorme, Odile Boute, Cindy Colson, Florence Petit, Marine Legendre, Sophie Naudion, Caroline Rooryck, Clément Prouteau, Estelle Colin, Agnès Guichet, Alban Ziegler, Dominique Bonneau, Godelieve Morel, Mélanie Fradin, Alinoé Lavillaureix, Chloé Quelin, Laurent Pasquier, Sylvie Odent, Gabriella Vera, Alice Goldenberg, Anne-Marie Guerrot, Anne-Claire Brehin, Audrey Putoux, Jocelyne Attia, Carine Abel, Patricia Blanchet, Constance F. Wells, Caroline Deiller, Mathilde Nizon, Mathilde Nizon, Sandra Mercier, Sandra Mercier, Marie Vincent, Marie Vincent, Bertrand Isidor, Bertrand Isidor, Jeanne Amiel, Jeanne Amiel, Rodolphe Dard, Manon Godin, Nicolas Gruchy, Médéric Jeanne, Médéric Jeanne, Elise Schaeffer, Pierre-Yves Maillard, Frédérique Payet, Marie-Line Jacquemont, Christine Francannet, Sabine Sigaudy, Marine Bergot, Marine Bergot, Emilie Tisserant, Marie-Laure Ascencio, Christine Binquet, Yannis Duffourd, Yannis Duffourd, Christophe Philippe, Christophe Philippe, Laurence Faivre, Laurence Faivre, Christel Thauvin-Robinet, Christel Thauvin-Robinet, Christel Thauvin-Robinet   +84 more
doaj   +1 more source

Estimating process‐based model parameters from species distribution data using the evolutionary algorithm CMA‐ES

Methods in Ecology and Evolution, 2023
Two main types of species distribution models are used to project species range shifts in future climatic conditions: correlative and process‐based models.
Victor Van der Meersch, Isabelle Chuine   +1 more
doaj   +1 more source

Alternative Restart Strategies for CMA-ES [PDF]

, 2012
This paper focuses on the restart strategy of CMA-ES on multi-modal functions. A first alternative strategy proceeds by decreasing the initial step-size of the mutation while doubling the population size at each restart. A second strategy adaptively allocates the computational budget among the restart settings in the BIPOP scheme.
Loshchilov, Ilya, Schoenauer, Marc, Sebag, Michèle   +2 more
openaire   +4 more sources

Constrained optimization of a zoom lens with CMA-ES algorithm [PDF]

EPJ Web of Conferences
In the present paper we investigate how optimization algorithm can be tailored to improve the lens design process. We replaced gradient-based optimization methods by the Covariance Matrix Adaptation Evolution Strategy (CMA-ES).
Marty Tristan, Héron Sébastien, Semet Yann   +2 more
doaj   +1 more source

Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy

Materials & Design, 2021
This paper introduces a new objective-driven design method based on deep learning for meta-structure absorber for X-band (8–12 GHz) application. The method consists of three steps; at Step 1, developing a simulator to predict a spectrum of microwave from
Han-Ik On, Leekyo Jeong, Minseok Jung, Dong-Joong Kang, Jun-Hyub Park, Hak-Joo Lee   +5 more
doaj   +1 more source

Genetic diagnosis of fetal microcephaly at a single tertiary center in China

Frontiers in Genetics, 2023
Background: Microcephaly is common in patients with neuropsychiatric problems, and it is usually closely related to genetic causes. However, studies on chromosomal abnormalities and single-gene disorders associated with fetal microcephaly are limited ...
You Wang, You Wang, Fang Fu, Tingying Lei, Li Zhen, Qiong Deng, Hang Zhou, Chunling Ma, Ken Cheng, Ken Cheng, Ruibin Huang, Ru Li, Qiuxia Yu, Lushan Li, Jin Han, Xin Yang, Dongzhi Li, Can Liao, Can Liao   +18 more
doaj   +1 more source

Enhancing Graph Routing Algorithm of Industrial Wireless Sensor Networks Using the Covariance-Matrix Adaptation Evolution Strategy

Sensors, 2022
The emergence of the Industrial Internet of Things (IIoT) has accelerated the adoption of Industrial Wireless Sensor Networks (IWSNs) for numerous applications.
Nouf Alharbi, Lewis Mackenzie, Dimitrios Pezaros   +2 more
doaj   +1 more source

Modified Covariance Matrix Adaptation – Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design

International Journal for Simulation and Multidisciplinary Design Optimization, 2015
The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(λ, μ) optimization algorithm is proposed in order to efficiently handle the constraints in the presence of noise.
Chocat Rudy, Brevault Loïc, Balesdent Mathieu, Defoort Sébastien   +3 more
doaj   +1 more source