國立虎尾科技大學 |

Improving System of Systems Progress : = Dynamically Modeling, Predicting and Affecting Rate of Convergence.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Improving System of Systems Progress :/
Reminder of title:	Dynamically Modeling, Predicting and Affecting Rate of Convergence.
Author:	Collins, Bernard F., II.
Description:	1 online resource (151 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
Subject:	Systems science. -
Online resource:	click for full text (PQDT)
ISBN:	9780355479522

Improving System of Systems Progress : = Dynamically Modeling, Predicting and Affecting Rate of Convergence.
Collins, Bernard F., II.

Improving System of Systems Progress :Dynamically Modeling, Predicting and Affecting Rate of Convergence. - 1 online resource (151 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

A systems engineer must identify effective techniques for improving the convergence of a System of Systems (SoS). The effectiveness of the identified techniques needs to be quantified so that the stakeholders may make informed cost benefit decisions. Exploring outer worlds, defending from asymmetric threats, utilizing waning natural resources, or instantly identifying an individual's esoteric ailment all require complicated and expansive cyber-physical-social systems. The magnitude and enormity of these challenges dictate that these systems be architected of other systems, constituent systems, that converge to become an SoS. An architect must predict the rate of convergence of the constituent systems needed in order to achieve the desired functionality in a cost-effective timeframe. The architect must also be able to evaluate the SoS progress and be perceptive to methods for improving their approach.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355479522Subjects--Topical Terms:

1148479
Systems science.
Index Terms--Genre/Form:

554714
Electronic books.

Improving System of Systems Progress : = Dynamically Modeling, Predicting and Affecting Rate of Convergence.
LDR:04240ntm a2200373Ki 4500 001 911307
005 20180529081902.5
006 m o u
007 cr mn||||a|a||
008 190606s2018 xx obm 000 0 eng d
020 $a 9780355479522
035 $a (MiAaPQ)AAI10638502
035 $a (MiAaPQ)gwu:13838
035 $a AAI10638502
040 $a MiAaPQ $b eng $c MiAaPQ
099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Collins, Bernard F., II. $3 1183026
245 1 0 $a Improving System of Systems Progress : $b Dynamically Modeling, Predicting and Affecting Rate of Convergence.
264 0 $c 2018
300 $a 1 online resource (151 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
500 $a Advisers: Steven Doskey; James Moreland.
502 $a Thesis (Ph.D.) $c The George Washington University $d 2018.
504 $a Includes bibliographical references
520 $a A systems engineer must identify effective techniques for improving the convergence of a System of Systems (SoS). The effectiveness of the identified techniques needs to be quantified so that the stakeholders may make informed cost benefit decisions. Exploring outer worlds, defending from asymmetric threats, utilizing waning natural resources, or instantly identifying an individual's esoteric ailment all require complicated and expansive cyber-physical-social systems. The magnitude and enormity of these challenges dictate that these systems be architected of other systems, constituent systems, that converge to become an SoS. An architect must predict the rate of convergence of the constituent systems needed in order to achieve the desired functionality in a cost-effective timeframe. The architect must also be able to evaluate the SoS progress and be perceptive to methods for improving their approach.
520 $a This research developed a model for quantifying and predicting the time-phased convergence of an SoS. The rate of convergence of an SoS depends on the Political, Economic, Social and Technological (PEST) environments surrounding the SoS and thereby influencing the decisions and attitudes of the stakeholders of the constituent systems. Under the influence of the PEST environment, the stakeholders of constituent systems choose to invest in connectivity and choose to belong. The rate of convergence of the SoS was modeled with a Dynamic Bayesian Network (DBN). The time-tagged factors which established the PEST environment were used as the inputted events and the time-phased convergence of the SoS was defined to be the outcome. The model could then be used to predict the future convergence based on expectations of the PEST environment. The model could also be used to identify what would need to change in the PEST environment in order to realize a desired or prescribed future rate of convergence.
520 $a A quantified case study was performed using the U.S. Smart Grid. The U.S. Smart Grid is a developing National-level SoS. The constituent systems are the electric grids of the fifty States. The PEST environment was described by collecting time-tagged PEST factors. The convergence of the U.S. Smart Grid was quantified through the grid's Advanced Metering Infrastructure (AMI). A validated DBN was used to predict the future convergence of the U.S. Smart Grid. The DBN was also used to quantify the effect that changes to the PEST factors would have on the rate of convergence and to suggest ways to improve the rate of convergence.
520 $a The functionality of an SoS emerges from the convergence of constituent systems. This research shows that the rate of convergence of an SoS can be modeled. A system engineer may use the information from such a model to inform investment decisions and to quantify the effect of proposals to influence the rate of convergence.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Systems science. $3 1148479
655 7 $a Electronic books. $2 local $3 554714
690 $a 0790
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The George Washington University. $b Systems Engineering. $3 1148622
773 0 $t Dissertation Abstracts International $g 79-03B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10638502 $z click for full text (PQDT)