Analysis and evaluation of net‐centric command and control decision processes

Analysis and evaluation of net‐centric command and control decision processes Purpose – The purpose of this paper is to present an approach which can evaluate the ability that successfully achieves command and control, both in qualitative and quantitative modes, to improve decision accuracy and speed, as well as construct an executable architecture for analyzing and verifying different decision projects. Design/methodology/approach – By defining command and control (C2) decision architecture and decomposing C2 decision processes into measurable subfunctions, measures and metrics will be associated with each of the lowest level decomposed functions, and will be used to provide support for performance evaluation. Both Markov decision process analysis and conditional probability (CP) logic are used for modeling the decision‐making process of course of action (COA). Meanwhile, an executable architecture constructed by Petri net is applied to logic structural verification and performance evaluation. Findings – The paper presents an idea and methodology for net‐centric command and control decision‐making process analysis. Research limitations/implications – The paper describes and decomposes C2 decision processes for complex missions in uncertain environments. Practical implications – The paper could be an important reference of analysis and application in net‐centric command and control of decision making. Originality/value – The paper combines methodology with qualitative methods (decision process decomposition), quantitative method (Markov decision process analysis and CP logic), as well as structural verification and performance evaluation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Analysis and evaluation of net‐centric command and control decision processes

Kybernetes, Volume 41 (9): 7 – Oct 12, 2012

Loading next page...
 
/lp/emerald-publishing/analysis-and-evaluation-of-net-centric-command-and-control-decision-T3Y3JcU1QA
Publisher
Emerald Publishing
Copyright
Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.
ISSN
0368-492X
DOI
10.1108/03684921211275333
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to present an approach which can evaluate the ability that successfully achieves command and control, both in qualitative and quantitative modes, to improve decision accuracy and speed, as well as construct an executable architecture for analyzing and verifying different decision projects. Design/methodology/approach – By defining command and control (C2) decision architecture and decomposing C2 decision processes into measurable subfunctions, measures and metrics will be associated with each of the lowest level decomposed functions, and will be used to provide support for performance evaluation. Both Markov decision process analysis and conditional probability (CP) logic are used for modeling the decision‐making process of course of action (COA). Meanwhile, an executable architecture constructed by Petri net is applied to logic structural verification and performance evaluation. Findings – The paper presents an idea and methodology for net‐centric command and control decision‐making process analysis. Research limitations/implications – The paper describes and decomposes C2 decision processes for complex missions in uncertain environments. Practical implications – The paper could be an important reference of analysis and application in net‐centric command and control of decision making. Originality/value – The paper combines methodology with qualitative methods (decision process decomposition), quantitative method (Markov decision process analysis and CP logic), as well as structural verification and performance evaluation.

Journal

KybernetesEmerald Publishing

Published: Oct 12, 2012

Keywords: Decision support systems; Decision making; Decision‐making process; Function decomposition; Belief vector; Conditional probability; Petri net; Performance evaluation

References

  • Information, prediction and structural whole: an introduction
    Lin, Y.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off