PuSH - Publication Server of Helmholtz Zentrum München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Zhao, Y.* ; Zhu, Z.* ; Chen, B.* ; Qiu, S.* ; Huang, J.* ; Lu, X.* ; Yang, W.* ; Ai, C.* ; Huang, K.* ; He, C. ; Jin, Y.* ; Liu, Z.* ; Wang, F.Y.*

Toward parallel intelligence: An interdisciplinary solution for complex systems.

Innovation 4:100521 (2023)
Publ. Version/Full Text DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling, analysis, management, and control. To meet these demands, the parallel systems method rooted in the artificial systems, computational experiments, and parallel execution (ACP) approach has been developed. The method cultivates a cycle termed parallel intelligence, which iteratively creates data, acquires knowledge, and refines the actual system. Over the past two decades, the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines, offering versatile interdisciplinary solutions for complex systems across diverse fields. This review explores the origins and fundamental concepts of the parallel systems method, showcasing its accomplishments as a diverse array of parallel technologies and applications while also prognosticating potential challenges. We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.
Impact Factor
Scopus SNIP
Altmetric
33.100
0.000
Tags
Annotations
Special Publikation
Hide on homepage

Edit extra information
Edit own tags
Private
Edit own annotation
Private
Hide on publication lists
on hompage
Mark as special
publikation
Publication type Article: Journal article
Document type Review
Keywords Computational Social-science; Of-the-art; Transportation Systems; Knowledge Automation; Autonomous Vehicles; Evacuation; Framework; Organizations; Metaverses; Scenarios
Language english
Publication Year 2023
HGF-reported in Year 2023
ISSN (print) / ISBN 2666-6758
e-ISSN 2666-6758
Journal Innovation
Quellenangaben Volume: 4, Issue: 6, Pages: , Article Number: 100521 Supplement: ,
Publisher Zeiss
Publishing Place 50 Hampshire St, Floor 5, Cambridge, Ma 02139 Usa
Institute(s) Institute of Epidemiology (EPI)
POF-Topic(s) 30202 - Environmental Health
Research field(s) Genetics and Epidemiology
PSP Element(s) G-504000-001
Grants Hunan Science and Technology Plan project
National Social Science Foundation of China
Social Science Foundation of Shanghai
National Major Research & Develop- ment Program of China, Social Science Foundation of Shanghai
Special Key Project of Biosafety Technologies for the National Major Research & Development Program of China
National Natural Science Foundation of China
DOI 10.1016/j.xinn.2023.100521
WOS ID 001108635100001
Scopus ID 85174437799
PubMed ID 37915363
Erfassungsdatum 2023-11-28
[➜Report correction]