Results 121 to 130 of about 5,432,397 (302)
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
Efficient Estimation of Copula-based Semiparametric Markov Models [PDF]
This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant (one-dimensional marginal) distributions and parametric bivariate copula functions ...
Yanping Yi, Xiaohong Chen, Wei Biao Wu
core
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Gas lift is extensively used in the oil & gas industry to draw oil/gas from old wells. It comprises a compressor driven by an engine. This paper presents reliability analysis of a system consisting of three gas lifts operating in parallel.
S Z Taj, S M Rizwan, Mohamed Al Ismaili
doaj +1 more source
Markov or not Markov - this should be a question [PDF]
Although it is well known that Markov process theory, frequently applied in the literature on income convergence, imposes some very restrictive assumptions upon the data generating process, these assumptions have generally been taken for granted so far ...
Bickenbach, Frank, Bode, Eckhardt
core
Abstract Large‐scale land reforms constitute a substantial redistribution of wealth and reallocation of agricultural land, which is a major form of asset and production input in developing countries. While land redistribution (from the rich to the poor) remains a highly controversial issue, extensive evidence on its effect is limited.
Devashish Mitra +3 more
wiley +1 more source
Consistent Markov Edge Processes and Random Graphs
We discuss Markov edge processes {Ye;e∈E} defined on edges of a directed acyclic graph (V,E) with the consistency property PE′(Ye;e∈E′)=PE(Ye;e∈E′) for a large class of subgraphs (V′,E′) of (V,E) obtained through a mesh dismantling algorithm.
Donatas Surgailis
doaj +1 more source
ON SEMI-MARKOV PROCESSES [PDF]
openaire +3 more sources
Abstract Mixed evidence for the influence of structural and social factors on adolescent substance use behaviors exists across the rural–urban continuum. Therefore, this study explores how adolescent perceptions of structural and social community risk factors are associated with lifetime and past 30‐day use of alcohol, marijuana, cigarettes, and ...
Melissa Pearman Fenton +4 more
wiley +1 more source

