A threat assessment method of group targets based on interval-valued intuitionistic fuzzy multi-attribute group decision-making

Kong, Depeng; Chang, Tianqing; Wang, Quandong; Sun, Huiyong; Dai, Wenjun

doi:10.1016/j.asoc.2018.03.015

Cited by 55 publications

(23 citation statements)

References 58 publications

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“…Kong et al deal with the issue of threat assessment of group target that is consisted of multiclass weapons. Assessing the threat of group target is for the optimal decision of troop deployment.…”

Section: Related Workmentioning

confidence: 99%

A Dempster‐Shafer theory and uninorm‐based framework of reasoning and multiattribute decision‐making for surveillance system

Liu

Luo

et al. 2019

Int J Intell Syst

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Closed-circuit television and sensor-based intelligent surveillance systems have attracted considerable attentions in the field of public security affairs. To provide real-time reaction in the case of a huge volume of the surveillance data, researchers have proposed eventreasoning frameworks for modeling and inferring events of interest. However, they do not support decisionmaking, which is very important for surveillance operators. To this end, this paper incorporate a function of decision-making in an event-reasoning framework, so that our model not only can perform event-reasoning but also can predict, rank, and alarm threats according to uncertain information from multiple heterogeneous sources. In particular, we propose a multiattribute decision-making model, in which an object being watched is modeled as a multiattribute event, where each attribute corresponds to a specific source, and the information from each source can be used to elicit a local threat degree of different malicious situations with respect to the corresponding attribute. Moreover, to assess an overall threat degree of an object being observed, we also propose a method to fuse the conflict threat degrees regarding all the relevant attributes.

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Section: Related Workmentioning

confidence: 99%

A Dempster‐Shafer theory and uninorm‐based framework of reasoning and multiattribute decision‐making for surveillance system

Liu

Luo

et al. 2019

Int J Intell Syst

View full text Add to dashboard Cite

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“…In this paper, the membership function µ(x i ) represents the threat level of the ith target x i . The threat assessment algorithm based on intuitionistic fuzzy set [23] is used to obtain the weight of target attributes, and then the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) model [24] is used to assess target threats. For the details of the threat assessment algorithm, please refer to [25].…”

Section: Dynamic Three-way Decision Modelmentioning

confidence: 99%

A Task Scheduling Algorithm for Phased-Array Radar Based on Dynamic Three-Way Decision

Tian

Chen

et al. 2019

Sensors

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The time resource management of phased-array radars is the key to fulfilling their performance, such as how phased-array radar can efficiently and reasonably schedule tasks under limited resources. Therefore, this paper proposes a task scheduling algorithm for phased-array radar based on dynamic three-way decision. The algorithm introduces three-way decision into the scheduling algorithm and divides the target into three threat areas according to the threat degree (i.e., threat area, nonthreat area, and potential threat area). Different threat domains are assigned different weights and combine the working mode and the task deadline to carry out comprehensive priority planning, so that the radar can reasonably allocate time according to the difference of the target threat level and the threat area in the tracking stage. In addition, an improved adaptive threshold algorithm is proposed to obtain a dynamic three-way decision to achieve the adaptation of the algorithm. A set of performance indicators have been defined to evaluate the algorithm. The relevant experiments have demonstrated that the proposed algorithm can effectively improve the processing capability of phased-array radars when dealing with high-threat targets.

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“…Finally, based on these grey correlation coefficients, we calculate the grey correlation level. Figure 5 shows the grey relational analysis process [ 61 ].…”

Section: Preliminariesmentioning

confidence: 99%

Novel Method for Perceiving Key Requirements of Customer Collaboration Low-Carbon Product Design

Liu

Zhu

et al. 2018

IJERPH

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Low-carbon product design is an important way to reduce greenhouse gas emission. Customer collaborative product innovation (CCPI) has become a new worldwide product design trend. Based on this popularity, we introduced CCPI into the low-carbon product design process. An essential step for implementing low carbon CCPI is to clarify key low carbon requirements of customers. This study tested a novel method for perceiving key requirements of customer collaboration low-carbon product design based on fuzzy grey relational analysis and genetic algorithm. Firstly, the study considered consumer heterogeneity, allowing different types of customers to evaluate low carbon requirements in appropriate formats that reflected their degrees of uncertainty. Then, a nonlinear optimization model was proposed to establish the information aggregation factor of customers based on the genetic algorithm. The weight of customers was obtained simultaneously. Next, the key low carbon requirements of customer were identified. Finally, the effectiveness of the proposed method was illustrated with a case related to a low carbon liquid crystal display.

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A threat assessment method of group targets based on interval-valued intuitionistic fuzzy multi-attribute group decision-making

Cited by 55 publications

References 58 publications

A Dempster‐Shafer theory and uninorm‐based framework of reasoning and multiattribute decision‐making for surveillance system

A Dempster‐Shafer theory and uninorm‐based framework of reasoning and multiattribute decision‐making for surveillance system

A Task Scheduling Algorithm for Phased-Array Radar Based on Dynamic Three-Way Decision

Novel Method for Perceiving Key Requirements of Customer Collaboration Low-Carbon Product Design

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