Results 71 to 80 of about 193,674 (278)

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Subgeometric Ergodicity under Random-Time State-Dependent Drift Conditions

Journal of Probability and Statistics, 2014
Motivated by possible applications of Lyapunov techniques in the stability of stochastic networks, subgeometric ergodicity of Markov chains is investigated.
Mokaedi V. Lekgari
doaj   +1 more source

Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 more
wiley   +1 more source

Forecasting land use and land cover change as a tool for optimising adaptation to climate change: Examples of selected Second-Tier Cities of the V4 Group

Bulletin of Geography. Socio-Economic Series
Second-tier cities are an important element in the socio-economic development of each country, including V4 countries. The result is a dynamic change in land use/cover patterns.
Marcin Feltynowski, Agnieszka Rzeńca, Agnieszka Palma   +2 more
doaj   +1 more source

Subgeometric Ergodicity Analysis of Continuous-Time Markov Chains under Random-Time State-Dependent Lyapunov Drift Conditions

Journal of Probability and Statistics, 2014
We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs). We are mainly concerned with making use of the available results on deterministic state-dependent drift ...
Mokaedi V. Lekgari
doaj   +1 more source

Structure and eigenvalues of heat-bath Markov chains

, 2014
We prove that heat-bath chains (which we define in a general setting) have no negative eigenvalues. Two applications of this result are presented: one to single-site heat-bath chains for spin systems and one to a heat-bath Markov chain for sampling ...
Dyer, Martin, Greenhill, Catherine, Ullrich, Mario   +2 more
core   +1 more source

Rowmotion Markov chains

Advances in Applied Mathematics
20 pages, 4 figures. The new version introduces and studies toggle Markov chains and proves cutoff for rowmotion Markov chains of Boolean ...
Defant, Colin, Li, Rupert, Nestoridi, Evita   +2 more
openaire   +3 more sources

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

PageRank of Gluing Networks and Corresponding Markov Chains

Mathematics
This paper studies Google’s PageRank algorithm. By an innovative application of the method of gluing Markov chains, we study the properties of Markov chains and extend their applicability by accounting for the damping factor and the personalization ...
Xuqian Ben Han, Shihao Wang, Chenglong Yu   +2 more
doaj   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source