Results 81 to 90 of about 9,274 (303)

Molecular Dynamics Simulations of γ‐Belite(010)–Water Interfaces With High‐Dimensional Neural Network Potentials

Chemistry – A European Journal, EarlyView.
Several γ$\gamma$‐belite(010)–water interfaces have been studied by molecular dynamics simulations using a high‐dimensional neural network potential. The structure and reactivity of interfacial water have been analyzed and two types of surface defects could be identified, which indicate the possible existence of a wide range of surface structures ...
Bernadeta Prus, Jörg Behler
wiley   +1 more source

Application of Improved Deep Neural Network in Complex Chemical Soft Measurement

Chemical Engineering Transactions, 2018
To improve the application effect of deep neural network in complex chemical soft measurement. After Kalman filtering equations were introduced, the algorithms of extended Kalman filter, volumetric Kalman filter and square root volumetric Kalman filter ...
Xilong Ding
doaj   +1 more source

Image Binarisation using the Extended Kalman Filter [PDF]

, 2007
Form design is frequently carried out through paper sketches of the designer’s mental model of an object. To improve the time it takes from solution concept to production it would therefore be beneficial if paperbased sketches can be automatically interpreted for importation into three-dimensional geometric computer aided design (CAD) systems.
Bartolo, Alexandra, Camilleri, Kenneth P., Camilleri, Tracey A., Fabri, Simon G., Borg, Jonathan C., 2nd International Conference on Informatics in Control, Automation and Robotics (ICINCO)   +5 more
openaire   +2 more sources

A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao, Debaprasad Dutta, Simant R. Upreti   +2 more
wiley   +1 more source

RFID Data-Driven Vehicle Speed Prediction via Adaptive Extended Kalman Filter

Sensors, 2018
The traditional speed prediction generally utilizes the Global Position System (GPS) and video images, and thus, the prediction precision mainly depends on environmental factors (i.e., weather, ionosphere, troposphere, air, and electromagnetic waves). We
Yupin Huang, Liping Qian, Anqi Feng, Yuan Wu, Wei Zhu   +4 more
doaj   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Filtering in Finance. [PDF]

In this article we present an introduction to various Filtering algorithms and some of their applications to the world of Quantitative Finance. We shall first mention the fundamental case of Gaussian noises where we obtain the well-known Kalman Filter ...
Javaheri, Alireza, Lautier, Delphine, Galli, Alain   +2 more
core  

Restauração de imagens via filtragem de Kalman e considerações sobre a avaliação da qualidade de imagens restauradas [PDF]

, 2003
Tese (doutorado) - Universidade Federal de Santa Catarina. Centro Tecnológico. Programa de Pós-Graduação em Engenharia Elétrica.A presente tese trata da utilização de programação evolucionária (PE) em sistemas de restauração de imagens via filtragem de ...
Zampolo, Ronaldo de Freitas
core  

Process fault prognosis using a fuzzy-adaptive unscented Kalman predictor [PDF]

, 2011
By monitoring the future process status via information prediction, process fault prognosis is able to give an early alarm and therefore prevent faults, when the faults are still in their early stages.
Sheng Chen, Xuemin Tian, Chen, Sheng, Tian, Xuemin, Cao, Yuping, Yu Ping Cao   +5 more
core   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source