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Journal ArticleDOI

Mission evaluation: expert evaluation system for large-scale combat tasks of the weapon system of systems

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TLDR
A system to assist military personnel in improving the efficiency of mission evaluation and the main innovations of this work include the qualitative and quantitative visualization of complex information is realized in a three-pane interface.
Abstract
Mission evaluation is a new requirement for capability evaluation of the weapon system of systems (WSOS) in the era of big data, and is based on evaluating large-scale tasks with similar attributes. The use of traditional methods by military experts to evaluate large scale tasks incurs significant time cost and results in low accuracy, and is caused by a variety of factors that cause confusion. Therefore, we developed a system to assist military personnel in improving the efficiency of mission evaluation; the main innovations of our work include the qualitative and quantitative visualization of complex information is realized in a three-pane interface. We also realize the iterative and interactive evaluation modes of large-scale tasks by using the active learning method; moreover, the overall display of large-scale task evaluation results is realized using statistical graphics. In practical application, the system not only improves the users’ efficiency and accuracy scores, but also helps to achieve the recognition evaluation for the overall scoring results.

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Citations
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Journal ArticleDOI

A Novel Weapon System Effectiveness Assessment Method Based on the Interval-Valued Evidential Reasoning Algorithm and the Analytical Hierarchy Process

TL;DR: In this article, the authors proposed a method that utilized the interval-valued evidential reasoning (ER) algorithm, the analytical hierarchy process (AHP), and the two-grade interval ranking method to properly deal with interval uncertainty in the assessment as well as provide reliable assessment results.
Journal ArticleDOI

Weapon system operational effectiveness evaluation based on the belief rule-based system with interval data

TL;DR: By introducing interval-valued evidential reasoning (ER) approach into belief rule-based system (BRBS), this paper proposed an intervals-valued BRB inference method for weapon system operational effectiveness evaluation.
Journal ArticleDOI

Evaluation of Anti-Tank Guided Missiles: An integrated Fuzzy Entropy and Fuzzy CoCoSo multi criteria methodology using technical and simulation data

TL;DR: In this paper , the authors proposed a comprehensive methodology consisting of 4 phases and 15 steps, using simulation and technical data, Fuzzy Shannon's Entropy (F-Entropy) based on α-level sets, and fuzzy CoCoSo with Bonferroni (FCoCoCoSo’B) methods for the selection of ATGMs to be used in the close quarter combat conditions.
Proceedings ArticleDOI

The Capability Concept in the Context of Systems of Systems: A Systematic Literature Review

TL;DR: In this paper , the authors look at the body of knowledge surrounding definitions, support systems and practices around the concept of capability in the context of systems of systems (SoS) and show that context dependent nature of the definition of capability, country-specific support systems, ongoing efforts to form more robust frameworks and dominant establishment of this theme in the defense sector.
References
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Active Learning Literature Survey

Burr Settles
TL;DR: This report provides a general introduction to active learning and a survey of the literature, including a discussion of the scenarios in which queries can be formulated, and an overview of the query strategy frameworks proposed in the literature to date.
Journal ArticleDOI

Queries and Concept Learning

TL;DR: This work considers the problem of using queries to learn an unknown concept, and several types of queries are described and studied: membership, equivalence, subset, superset, disjointness, and exhaustiveness queries.
Proceedings ArticleDOI

Support vector machine active learning for image retrieval

TL;DR: This work proposes the use of a support vector machine active learning algorithm for conducting effective relevance feedback for image retrieval and achieves significantly higher search accuracy than traditional query refinement schemes after just three to four rounds of relevance feedback.
Proceedings Article

Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions

TL;DR: This work combines active and semi-supervised learning techniques under a Gaussian random field model, which requires a much smaller number of queries to achieve high accuracy compared with random query selection.
Proceedings ArticleDOI

Multi-class active learning for image classification

TL;DR: An uncertainty measure is proposed that generalizes margin-based uncertainty to the multi-class case and is easy to compute, so that active learning can handle a large number of classes and large data sizes efficiently.