English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems

Hellmann, F., Zolotarevskaia, E., Kurths, J., Raisch, J. (2023): Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems. - Journal of Physics: Complexity, 4, 2, 025007.
https://doi.org/10.1088/2632-072X/acccc9

Item is

Files

show Files
hide Files
:
28348oa.pdf (Publisher version), 16MB
Name:
28348oa.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Hellmann, Frank1, Author              
Zolotarevskaia, Ekaterina1, Author              
Kurths, Jürgen1, Author              
Raisch, Jörg2, Author
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: Given two dynamical systems, we quantify how similar they are with respect to their interaction with the outside world. We focus on the case where simpler systems act as a specification for a more complex one. Combining a behavioral and probabilistic perspective we define several useful notions of the distance of a system to a specification. We show that these distances can be used to tune a complex system. We demonstrate that our approach can successfully make non-linear networked systems behave like much smaller networks, allowing us to aggregate large sub-networks into one or two effective nodes. Finally, we discuss similarities and differences between our approach and H∞ model reduction.

Details

show
hide
Language(s): eng - English
 Dates: 2023-04-132023-04-132023-04-27
 Publication Status: Finally published
 Pages: 13
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/2632-072X/acccc9
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Working Group: Dynamics, stability and resilience of complex hybrid infrastructure networks
Research topic keyword: Complex Networks
Research topic keyword: Energy
Research topic keyword: Nonlinear Dynamics
OATYPE: Gold Open Access
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Physics: Complexity
Source Genre: Journal, other, oa
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 4 (2) Sequence Number: 025007 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journal-physics-complexity
Publisher: IOP Publishing