Results 71 to 80 of about 414,285 (246)

Applications of Voronoi Diagrams in Multi-Robot Coverage: A Review

Journal of Marine Science and Engineering
In recent decades, multi-robot region coverage has played an important role in the fields of environmental sensing, target searching, etc., and it has received widespread attention worldwide.
Meng Zhou, Jianyu Li, Chang Wang, Jing Wang, Li Wang   +4 more
doaj   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

UV-Diagram: A Voronoi Diagram for Uncertain Spatial Databases

, 2013
The Voronoi diagram is an important technique for answering nearest-neighbor queries for spatial databases. We study how the Voronoi diagram can be used for uncer-tain spatial data, which are inherent in scientific and business applications. Specifically,
Xie, Scott, Xike, Yiu, ML, Liwen Sun, Cheng, R, Sun, L, Xie, X, Yiu, Man Lung, Reynold Cheng, Jinchuan Chen, Chen, J, Xike Xie, Man Lung Yiu, Cheng, Reynold, Sun, Liwei, Chen, Jinchuan   +14 more
core   +1 more source

UV-diagram: A Voronoi diagram for uncertain data [PDF]

, 2010
The Voronoi diagram is an important technique for answering nearest-neighbor queries for spatial databases. In this paper, we study how the Voronoi diagram can be used on uncertain data, which are inherent in scientific and business applications.
Xie, X, Chen, J, Reynold Cheng, Jinchuan Chen, Yiu, ML, Xike Xie, Liwen Sun, Cheng, R, Man Lung Yiu, Sun, L   +9 more
core   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Estratégia para divisão de áreas de estudo em problemas logísticos: uso do diagrama de Voronoi com obstáculos [PDF]

, 2004
Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.Compreendendo a eficácia do uso do Diagrama de Voronoi na obtenção de soluções em Logística, a presente tese, além de ...
Silva, Arinei Carlos Lindbeck da
core  

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

An efficient algorithm for approximate Voronoi diagram construction on triangulated surfaces

Computational Visual Media, 2023
Voronoi diagrams on triangulated surfaces based on the geodesic metric play a key role in many applications of computer graphics. Previous methods of constructing such Voronoi diagrams generally depended on having an exact geodesic metric. However, exact
Wenlong Meng, Pengbo Bo, Xiaodong Zhang, Jixiang Hong, Shiqing Xin, Changhe Tu   +5 more
doaj   +1 more source

Emergent Form from Structural Optimisation of the Voronoi Polyhedra Structure [PDF]

, 2007
In the course of the exploration of computational means in the architectural design process, in order to investigate more complex, adaptive geometries, the Voronoi diagram has recently gained some attention, being a three-dimensional space-filling ...
Derix, C, Hanna, S, Friedrich, E
core  

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

Advanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou, Qiang Gao, Liuchao Jin, Guoquan Xie, Kang Zhang, Wei‐Hsin Liao   +5 more
wiley   +1 more source