Develo** a national data-driven construction safety management framework with interpretable fatal accident prediction

K Koc, Ö Ekmekcioğlu, AP Gurgun - Journal of Construction …, 2023 - ascelibrary.org
Occupational accidents are frequent in the construction industry, containing significant risks
in the working environment. Therefore, early designation, taking preventive actions, and …

On distributed computing continuum systems

S Dustdar, VC Pujol, PK Donta - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article presents our vision on the need of develo** new managing technologies to
harness distributed “computing continuum” systems. These systems are concurrently …

The selection of industry 4.0 technologies through Bayesian networks: an operational perspective

P De Giovanni, V Belvedere… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Many manufacturing firms today are considering whether to adopt one or more technologies
associated with the Industry 4.0 vision. Yet, neither academic nor practitioner literature …

An efficient Bayesian network structure learning algorithm based on structural information

W Fang, W Zhang, L Ma, Y Wu, K Yan, H Lu… - Swarm and Evolutionary …, 2023 - Elsevier
Bayesian networks (BNs) are probabilistic graphical models regarded as some of the most
compelling theoretical models in the field of representation and reasoning under uncertainty …

Does supply chain matter for environmental firm performance: mediating role of financial development in China

W Zhao, ZS Luo, Q Liu - Economic Change and Restructuring, 2023 - Springer
The purpose of this research is to understand the impact of technological innovation on
corporate social responsibility and corporate environmental performance, as well as the …

A novel population robustness-based switching response framework for solving dynamic multi-objective problems

H Li, Z Fang, L Hu, H Liu, P Wu, N Zeng - Neurocomputing, 2024 - Elsevier
In this paper, a novel population robustness-based switching response framework (PR-SRF)
is proposed to develop effective dynamic multi-objective optimization algorithm (DMOA) …

Multi-Agent Genetic Algorithm for Bayesian networks structural learning

JPAF Campos, IG Machado, M Bessani - Knowledge-Based Systems, 2025 - Elsevier
Bayesian networks (BNs) are a powerful probabilistic graphical tool for modeling
relationships between random variables in an interpretable way. The relationships among …

[PDF][PDF] Self-Awakened Particle Swarm Optimization BN Structure Learning Algorithm Based on Search Space Constraint.

K Liu, P Li, Y Zhang, J Ren, X Wang… - Computers, Materials & …, 2023 - cdn.techscience.cn
To obtain the optimal Bayesian network (BN) structure, researchers often use the hybrid
learning algorithm that combines the constraint-based (CB) method and the score-and …

Real-time water demand pattern estimation using an optimized extended Kalman filter

F Attarzadeh, AN Ziaei, K Davary… - Expert Systems with …, 2024 - Elsevier
This study presents a hybrid approach for the estimation of real-time water demand
multipliers using the Kalman filter (KF) and extended Kalman filter (EKF). Multiple Linear …

[HTML][HTML] Higher Education in China during the Pandemic: Analyzing Online Self-Learning Motivation Using Bayesian Networks

J Li, Y Chang, S Liu, C Cai, Q Zhou, X Cai, W Lai, J Qi… - Sustainability, 2024 - mdpi.com
The COVID-19 pandemic has led to an unprecedented shift towards online learning,
compelling university students worldwide to engage in self-directed learning within remote …