Computational Intelligence and Neuroscience

Human Behavior Modelling in Engineering Management under Industry 4.0


Publishing date
01 Aug 2022
Status
Published
Submission deadline
08 Apr 2022

Lead Editor

1Central South University, Changsha, China

2City University of Hong Kong, Hong Kong

3Xi'an University of Architecture and Technology, Xian, China

4China University of Mining and Technology, Xuzhou, China

5London South Bank University, London, UK


Human Behavior Modelling in Engineering Management under Industry 4.0

Description

Human society is entering the era of Industry 4.0. Automatic production and intelligent manufacturing are proliferating rapidly across industries, freeing the workforce from simple but repetitive work. The roles of humans in engineering systems are continuously changing. In addition, engineering systems are becoming more intelligent and complex, which further increases the difficulties in engineering management. Engineering management is facing unprecedented opportunities and challenges. As humans are the most important and determining factor of management, human behavior can significantly affect the efficiency of engineering management.

However, it is usually not easy to understand the mechanism of decision-making process and human behavior in engineering management. This often requires interdisciplinary knowledge in engineering, management, neural engineering, mathematics, and psychology. Efficient tools for human behavior modelling and simulation are urgently needed. With the development of mathematical algorithms and computational technologies, intelligent modelling and simulation bring innovation to research on human behavior in engineering management. Specifically, advanced modelling and simulation methods, such as machine learning, deep learning, big data, system dynamics, and agent-based modelling, enable revealing the mechanism of decision-making process and predicting human behavior under various circumstances. Intelligent modelling and simulation provide valuable information and databases for managers to improve the efficiency of engineering management. There should be continuous research exploring applying intelligent techniques to model and simulate human behavior in engineering management.

The aim of this Special Issue is to solicit research and offer a timely opportunity to scholars and industry practitioners to discuss, share, and disseminate current innovations in intelligent modelling and simulation techniques for human behavior in engineering management under Industry 4.0. Authors are invited to present original research and review articles that will stimulate continuing efforts in this field. We hope that this Special Issue helps solve practical engineering problems and bring theoretical contributions.

Potential topics include but are not limited to the following:

  • Human behavior changes in engineering management under Industry 4.0
  • Intelligent modelling and simulation methods for human behavior in engineering management
  • Dynamic relationships between human behavior and the efficiency of engineering management under Industry 4.0
  • Machine learning and deep learning for human behavior in engineering management
  • Data mining for human behavior in engineering management
  • System dynamics for human behavior in engineering management
  • Agent-based modelling for human behaviour in engineering management
  • Complex employee relationship network modelling in engineering management under Industry 4.0
  • Intelligent prediction, monitoring, assessment, and management of human behavior in engineering management
  • Data-driven and intelligent decision support systems in engineering management under Industry 4.0

Articles

  • Special Issue
  • - Volume 2022
  • - Article ID 9572395
  • - Research Article

Design of Optimization Algorithm for Configuration of Amateur Sports Training Equipment in Smart City Community

Yuehong Wan | Hong Tang
  • Special Issue
  • - Volume 2022
  • - Article ID 8069007
  • - Research Article

A Data-Driven Customer Profiling Method for Offline Retailers

Huahong Zuo | Sike Yang | ... | Yingqiang Su
  • Special Issue
  • - Volume 2022
  • - Article ID 9230412
  • - Research Article

Research on the Training and Management of Industrializing Workers in Prefabricated Building with Machine Vision and Human Behaviour Modelling Based on Industry 4.0 Era

Junwu Wang | Yinghui Song | ... | Yipeng Liu
  • Special Issue
  • - Volume 2022
  • - Article ID 3436634
  • - Research Article

The Compound Effect of Spatial and Temporal Resolutions on the Accuracy of Urban Flood Simulation

Xiting Li | Leizhi Wang | ... | Lingjie Li
  • Special Issue
  • - Volume 2022
  • - Article ID 1869897
  • - Research Article

Portfolio Optimization Model for Gold and Bitcoin Based on Weighted Unidirectional Dual-Layer LSTM Model and SMA-Slope Strategy

Qianyi Xue | Yuewei Ling | Bingwei Tian
  • Special Issue
  • - Volume 2022
  • - Article ID 2249925
  • - Research Article

Research on an Intelligent Identification and Classification Method of Complex Holes in Triangle Meshes for 3D Printing

Shanhui Zhang | Wei Wei | Wei Wu
  • Special Issue
  • - Volume 2022
  • - Article ID 6928989
  • - Research Article

An Optimization Method for Enterprise Resource Integration Based on Improved Particle Swarm Optimization

Aifang Guo | Lina Zhu | Lingjie Chang
  • Special Issue
  • - Volume 2022
  • - Article ID 4398839
  • - Research Article

A Cooperative Lightweight Translation Algorithm Combined with Sparse-ReLU

Xintao Xu | Yi Liu | ... | Huaxiang Lu
  • Special Issue
  • - Volume 2022
  • - Article ID 5802217
  • - Research Article

High-Performance Concrete Strength Prediction Based on Machine Learning

Yanning Liu
  • Special Issue
  • - Volume 2022
  • - Article ID 4077516
  • - Research Article

Testing the Effects of the Digital Linguistic Landscape on Engineering Education for Smart Construction

Lin Xu | Jingxiao Zhang | ... | Ruoyu Jin

We have begun to integrate the 200+ Hindawi journals into Wiley’s journal portfolio. You can find out more about how this benefits our journal communities on our FAQ.