National Science Library of Georgia

Image from Google Jackets

Complex Adaptive Systems Modeling [electronic resource] / edited by Muaz A. Niazi.

Contributor(s): Material type: Continuing resourceContinuing resourcePublisher: Berlin/Heidelberg : Springer Berlin Heidelberg : Imprint: Springer. Description: online resourceISSN:
  • 2194-3206
Subject(s): Online resources: Summary: Complex Adaptive Systems Modeling (CASM) is a highly multidisciplinary modeling and simulation journal that serves as a unique forum for original, high-quality peer-reviewed papers with a specific interest and scope limited to agent-based and complex network-based modeling paradigms for Complex Adaptive Systems (CAS). The highly multidisciplinary scope of CASM spans any domain of CAS. Possible areas of interest range from the Life Sciences (E.g. Biological Networks and agent-based models), Ecology (E.g. Agent-based/Individual-based models), Social Sciences (Agent-based simulation, Social Network Analysis), Scientometrics (E.g. Citation Networks) to large-scale Complex Adaptive COmmunicatiOn Networks and environmentS (CACOONS) such as Wireless Sensor Networks (WSN), Body Sensor Networks, Peer-to-Peer (P2P) networks, pervasive mobile networks, service oriented architecture, smart grid and the Internet of Things. In general, submitted papers should have the following key elements:  A clear focus on a specific area of CAS E.g. ecology, social sciences, large scale communication networks, biological sciences etc.)  Either focus on an agent-based simulation model or else a complex network model based on data from CAS (e.g. Citation networks, Gene regulatory Networks, Social networks, Ecological Networks etc.). General guidelines for articles:  CASM has a strongly multidisciplinary editorial board and readership. Therefore authors need to be very careful that their articles have been written in a style that is comprehensible by a broad and multidisciplinary audience. Authors must avoid excessive usage of domain-specific jargon/terminologies without formally introducing these terms in the article. In addition, any concepts specific to a discipline must be explained in the article for the general readership of CASM. Thus, an article on Gene regulatory networks should be written with the goal that it may also be accessible to a number of social science researchers using Social Network Analysis and vice versa. Likewise an article written by Computer Scientists for Wireless sensor networks must also take into consideration CASM readership of researchers from Social and Biological Sciences and so on.  Authors are advised to use general terms (such as agent-based modeling and complex networks) instead of using domain-specific terms, wherever possible.  Submissions which are not in line with the above criteria or those which are of a purely or largely theoretical/Mathematical nature or have been written in a very domain specific manner or appear to have a limited audience may be considered as out of scope of CASM and rejected without review. For information regarding example topics and cover letter requirements, see Publication and peer review process, below.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

Complex Adaptive Systems Modeling (CASM) is a highly multidisciplinary modeling and simulation journal that serves as a unique forum for original, high-quality peer-reviewed papers with a specific interest and scope limited to agent-based and complex network-based modeling paradigms for Complex Adaptive Systems (CAS). The highly multidisciplinary scope of CASM spans any domain of CAS. Possible areas of interest range from the Life Sciences (E.g. Biological Networks and agent-based models), Ecology (E.g. Agent-based/Individual-based models), Social Sciences (Agent-based simulation, Social Network Analysis), Scientometrics (E.g. Citation Networks) to large-scale Complex Adaptive COmmunicatiOn Networks and environmentS (CACOONS) such as Wireless Sensor Networks (WSN), Body Sensor Networks, Peer-to-Peer (P2P) networks, pervasive mobile networks, service oriented architecture, smart grid and the Internet of Things. In general, submitted papers should have the following key elements:  A clear focus on a specific area of CAS E.g. ecology, social sciences, large scale communication networks, biological sciences etc.)  Either focus on an agent-based simulation model or else a complex network model based on data from CAS (e.g. Citation networks, Gene regulatory Networks, Social networks, Ecological Networks etc.). General guidelines for articles:  CASM has a strongly multidisciplinary editorial board and readership. Therefore authors need to be very careful that their articles have been written in a style that is comprehensible by a broad and multidisciplinary audience. Authors must avoid excessive usage of domain-specific jargon/terminologies without formally introducing these terms in the article. In addition, any concepts specific to a discipline must be explained in the article for the general readership of CASM. Thus, an article on Gene regulatory networks should be written with the goal that it may also be accessible to a number of social science researchers using Social Network Analysis and vice versa. Likewise an article written by Computer Scientists for Wireless sensor networks must also take into consideration CASM readership of researchers from Social and Biological Sciences and so on.  Authors are advised to use general terms (such as agent-based modeling and complex networks) instead of using domain-specific terms, wherever possible.  Submissions which are not in line with the above criteria or those which are of a purely or largely theoretical/Mathematical nature or have been written in a very domain specific manner or appear to have a limited audience may be considered as out of scope of CASM and rejected without review. For information regarding example topics and cover letter requirements, see Publication and peer review process, below.

There are no comments on this title.

to post a comment.
Copyright © 2023 Sciencelib.ge All rights reserved.