Results 61 to 70 of about 7,371,142 (245)

Dynamic Bayesian Networks for Musical Interaction [PDF]

, 2017
We describe in this chapter a consistent set of temporal models that we have developed over the years for analyzing movement in real-time musical interaction. These models are probabilistic and can be unified and generalized under the formalism of dynamic Bayesian networks (DBNs).
Caramiaux, Baptiste, Françoise, Jules, Bevilacqua, Frédéric   +2 more
openaire   +2 more sources

Multisensory integration using dynamical Bayesian networks [PDF]

Frontiers in Computational Neuroscience, 2015
Multisensory Integration (MSI) is the study of how information coming from different sensory modalities, such as vision, audition and etc. are being integrated by the nervous system (Stein et al., 2009) as a complex system. MSI is one of the most important aspects of neuroscience which has a great influence on our decision making system. It plays a key
Taher Abbas Shangari, Mohsen Falahi, Fatemeh Bakouie, Shahriar Gharibzadeh   +3 more
openaire   +4 more sources

Prediction of fatigue crack propagation based on dynamic Bayesian network

Advances in Mechanical Engineering, 2022
To address the problem of low prediction accuracy in the current research on fatigue crack propagation prediction, a prediction method of fatigue crack propagation based on a dynamic Bayesian network is proposed in this paper.
Wei Wang, Yanfang Yang, Mengzhen Li, Weikai Liu, Zhiping Liu   +4 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Towards data-centric control of sensor networks through Bayesian dynamic linear modelling [PDF]

, 2015
Wireless sensor networks usually operate in dynamic, stochastic environments. While the behaviour of individual nodes is important, they are better seen as contributors to a larger mission, and managing the sensing quality and performance of these ...
Dobson, Simon Andrew, Simon Dobson, Lei Fang, Fang, Lei   +3 more
core   +1 more source

A stochastic artificial neural network model for investigating street vendor behavior in a night market

International Journal of Distributed Sensor Networks, 2016
This article offers a hybrid computational approach that combines an artificial neural network with Bayesian probability to improve on the conventional artificial neural network model.
Pao-Kuan Wu, Tsung-Chih Hsiao, Ming Xiao
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Dynamic early warning of rockburst using microseismic multi-parameters based on Bayesian network

Engineering Science and Technology, an International Journal, 2021
Rockburst is a phenomenon where the elastic deformation may be emitted suddenly because of rock fragmentation, ejection, launching, and even earthquake.
Xiang Li, Haoyu Mao, Biao Li, Nuwen Xu
doaj   +1 more source

Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

Advanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang, Jianxiang Zhao, Zhaoqi Chen, Hao Gong, Yinsen Yan, Junlei Tao, Yong Yang   +6 more
wiley   +1 more source