Abstract

The prioritization of capability gaps for weapon system of systems is the basis for design and capability planning in the system of systems development process. In order to address input information uncertainties, the prioritization of capability gaps is computed in two steps using the conditional evidential network method. First, we evaluated the belief distribution of degree of required satisfaction for capabilities, and then calculated the reverse conditional belief function between capability hierarchies. We also provided verification for the feasibility and effectiveness of the proposed method through a prioritization of capability gaps calculation using an example of a spatial-navigation-and-positioning system of systems.

Highlights

  • A capability gap is defined by the degree to which a designated action plan of the system of systems cannot be implemented

  • The second aspect consists in comparing the status of the capability needs and the capabilities one by one, according to criteria, such as “be able to support well”, “be able to support under certain conditions”, and “cannot support”, as well as analyzing whether these capabilities support the completion of the task

  • In which we focused on the multiple uncertainties in the priority assessment of capability gaps, we adopted a method based on the conditional evidential network

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Summary

Introduction

A capability gap is defined by the degree to which a designated action plan of the system of systems cannot be implemented. Such a gap may result from a lack of capability, proficiency in existing capability solutions, and/or the need to replace existing capability solutions to prevent future gaps. It is a direct base for maximum capability realization of the system of systems. The first, in response to the functional needs of the capability, is to carry out an assessment of the capabilities in the weapon system of systems. The second aspect consists in comparing the status of the capability needs and the capabilities one by one, according to criteria, such as “be able to support well”, “be able to support under certain conditions”, and “cannot support”, as well as analyzing whether these capabilities support the completion of the task

Evidential Network
Prioritization Assessment of Capability Gaps
Basics of the Conditional Evidential Network
Capability Gaps Computing Based on the Conditional Evidential Network
Calculation of the Inverse Conditional Belief
Prioritization of System of Systems’ Capability Gaps
Case Study
The Construction of the Evidential-Network-Parameter Model
Capability-Requirement-Satisfaction Assessment
Comparison with the Bayesian Network Method
Results comparison
Calculation of the Inverse Conditional Belief Functions
Prioritization of Capability Gaps
Results
Result analysis
Full Text
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