Results 61 to 70 of about 404,944 (276)

Semi-Markov graph dynamics. [PDF]

PLoS ONE, 2011
In this paper, we outline a model of graph (or network) dynamics based on two ingredients. The first ingredient is a Markov chain on the space of possible graphs. The second ingredient is a semi-Markov counting process of renewal type. The model consists
Marco Raberto, Fabio Rapallo, Enrico Scalas   +2 more
doaj   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

AIChE Journal, EarlyView.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman, Zhe Li, Ilias Mitrai, Prodromos Daoutidis   +3 more
wiley   +1 more source

Markov chain comparison

, 2006
This is an expository paper, focussing on the following scenario. We have two Markov chains, $\mathcal {M}$ and $\mathcal {M}'$. By some means, we have obtained a bound on the mixing time of $\mathcal {M}'$.
Dyer, Martin, Goldberg, Leslie Ann, Jerrum, Mark, Martin, Russell   +3 more
core   +3 more sources

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

Markov chain analysis of regional climates [PDF]

Nonlinear Processes in Geophysics, 2010
We present a novel method for regional climate classification that is based on coarse-grained categorical representations of multivariate climate anomalies and a subsequent Markov chain analysis.
S. Mieruch, S. Noël, H. Bovensmann, J. P. Burrows, J. A. Freund   +4 more
doaj   +1 more source

Optimal control of multiple Markov-switching stochastic systems with numerical applications

Results in Control and Optimization, 2022
In this article the authors set up an optimal control framework for a hybrid stochastic system with dual or multiple Markov switching diffusion processes, while Markov chains governing these switching diffusions are not identical as assumed in the ...
Jianmin Shi
doaj   +1 more source

Markov Chain Monitoring

, 2018
In networking applications, one often wishes to obtain estimates about the number of objects at different parts of the network (e.g., the number of cars at an intersection of a road network or the number of packets expected to reach a node in a computer ...
Chaudhari, Harshal A., Mathioudakis, Michael, Terzi, Evimaria   +2 more
core   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Analisis Deteriorasi Perkerasan Jalan Tol Terdampak Banjir dengan Model Markov Chain Transisi Homogen dan Non-Homogen

Jurnal Teknik Sipil
Abstrak Model dan analisis yang mampu meramalkan dampak banjir terhadap kinerja perkerasan jalan raya, sangat penting untuk mengantisipasi penurunan kekuatan struktur perkerasan pasca terjadinya banjir.
Danang Saputro, Russ Bona Frazila, Febri Zukhruf   +2 more
doaj   +1 more source

STABILITY OF LINEAR SYSTEMS WITH MARKOVIAN JUMPS

Selecciones Matemáticas, 2016
In this work we will analyze the stability of linear systems governed by a Markov chain, this family is known in the specialized literature as linear systems with Markov jumps or by its acronyms in English MJLS as it is denoted in [1].
Jorge Enrique Mayta Guillermo
doaj   +1 more source