Interval TOPSIS with a novel interval number comprehensive weight for threat evaluation on uncertain information

2021 ◽  
pp. 1-17
Author(s):  
Chen Xiang ◽  
Wang Xing ◽  
Zhang Hubiao ◽  
Xu Yuheng ◽  
Chen You ◽  
...  
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Interval Number ◽  
Uncertain Information ◽  
Interval Numbers ◽  
Subjective Weight ◽  
Order Preference ◽  
The Mean ◽  
Deviation Method ◽  
Threat Evaluation

Threat evaluation (TE) is essential in battlefield situation awareness and military decision-making. The current processing methods for uncertain information are not effective enough for their excessive subjectivity and difficulty to obtain detailed information about enemy weapons. In order to optimize TE on uncertain information, an approach based on interval Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the interval SD-G1 (SD standard deviation) method is proposed in this article. By interval SD-G1 method, interval number comprehensive weights can be calculated by combining subjective and objective weights. Specifically, the subjective weight is calculated by interval G1 method, which is an extension of G1 method into interval numbers. And the objective weight is calculated by interval SD method, which is an extension of SD method with the mean and SD of the interval array defined in this paper. Sample evaluation results show that with the interval SD-G1 method, weights of target threat attributes can be better calculated, and the approach combining interval TOPSIS and interval SD-G1 can lead to more reasonable results. Additionally, the mean and SD of interval arrays can provide a reference for other fields such as interval analysis and decision-making.

scholarly journals A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Ease Of Use ◽  
Decision Makers ◽  
Ideal Solution ◽  
Interval Numbers ◽  
Group Matrix ◽  
Order Preference ◽  
Criteria Weights

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.

scholarly journals Extension Dependent Degree Method with Mapping Transformation for Three-Parameter Interval Number Decision Making

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Li-Bo Xu ◽  
Xing-Sen Li ◽  
Jun-kai Shao ◽  
Kai-jie Wang
Keyword(s):  
Decision Making ◽  
Interval Mapping ◽  
Transformation Method ◽  
Interval Number ◽  
Interval Numbers ◽  
New Approach ◽  
Dependent Function ◽  
Optimal Value ◽  
Decision Making Problem ◽  
Parameter Interval

In view of the multiattribute decision making problem that the attribute values and weights are both three-parameter interval numbers, a new decision making approach and framework based on extension simple dependent degree are proposed. According to traditional extension simple dependent function, the new approach proposes a new extension dependent function for three-parameter interval number. Then through an interval mapping transformation method, the process for obtaining dependent degree for the interval with its optimal value not being the endpoint is transformed to the monotonous process for the interval with its optimal value being the endpoint. The method can not only perform uncertain analysis of decision results by different settings of attitude coefficients, but also take dynamic analysis and rule finding by some extension transformation. At last, an example is presented to examine the effectiveness and stability of our method.

scholarly journals Using an improved interval technique for order preference by similarity to ideal solution to assess river ecosystem health

2019 ◽  
Vol 21 (4) ◽  
pp. 624-637
Author(s):  
Wei Xu ◽  
Zengchuan Dong ◽  
Li Ren ◽  
Jie Ren ◽  
Xike Guan ◽  
...  
Keyword(s):  
Ecosystem Health ◽  
Assessment System ◽  
Ideal Solution ◽  
River Ecosystem ◽  
Interval Numbers ◽  
Aquatic Life ◽  
Morphological Form ◽  
Standard Interval ◽  
Order Preference ◽  
The Mean

Abstract A river ecosystem health (REH) assessment system, based on indicators for morphological form, hydrology features, aquatic life, and habitat provision was established to characterize REH. The standard interval Technique for Order Preference by Similarity to Ideal Solution method (TOPSIS) does not fully consider dynamic changes in REH, so interval numbers and the mean were introduced into an improved version of TOPSIS to achieve a more objective analysis. The improved interval TOPSIS method was tested in the Zhangweinan River and a river ecosystem health integrated index (REHI) was calculated. The REHI decreased from 0.376 to 0.346 over the past 25 years and the REH ranged from general to poor for 1991 to 1995 and from poor to very poor for 1996 to 2000, 2001 to 2005, 2006 to 2010, and 2011 to 2015. The ecosystem health is poor because of dams and reservoirs in the upper reaches that prevent water flowing to the lower reaches, over-abstraction of water, and severe pollution. This method gives objective and accurate assessments of REH and can be used to support decision-making and evaluation in a range of fields.

scholarly journals Correlation of Medical Knowledge and Non-Technical Skills Assessment in Anesthesia Residents

2020 ◽  
Vol 72 (6) ◽  
pp. 483-487
Author(s):  
Kasana Raksamani ◽  
Tachawan Jirativanont ◽  
Pavinee Sareenun
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Rating Scale ◽  
Technical Skills ◽  
Skills Training ◽  
Skills Assessment ◽  
Task Management ◽  
Technical Skills Assessment ◽  
The Mean ◽  
Anesthesia Residents

Objective: Non-technical skills training and assessment has been implemented in anesthesia residency training program to improve quality of patient care but have not been properly assessed. We hypothesized that trainees with good knowledge correlated with good cognitive parts of non-technical skills.Methods: Seventy anesthesia residents (24 PGY-1, 24 PGY-2 and 22 PGY-3) were assessed for their knowledge by 180-item MCQs, 5 key-feature essay questions, and 18-station OSCE’s. Subsequently, a perioperative anesthesia crisis situation was set up in the simulation lab for all residents and was video recorded. Non-technical skills were assessed by 2 independent trained raters using Anesthetists’ Non-Technical Skills (ANTS) behavioral markers. The residents’ scores were calculated to find the correlation within the ANTS rating scale.Results: The mean scores of knowledge tests were 164.3 ±18.4 out of 300 [165.5 ±18.0, 154.7 ±16.3 and 173.6 ±16.4 for PGY-1, PGY-2 and PGY-3 respectively]. The mean scores of ANTS was divided into 4 categories (rating scale 1 to 4): task management 2.9 (±0.6), teamworking 3.0 (±0.5), situation awareness 2.9 (±0.8) and decision making 2.8 (±0.7). The knowledge test results moderately correlated with ANTS score in task management, situation awareness and decision making [r=0.382 (p<0.01), r=0.433 (p<0.001) and r=0.350 (p<0.01) respectively] and weakly correlated with the teamworking category (r=0.166, p=0.16).Conclusion: Resident’s scores showed moderate correlation with non-technical skills assessment results in cognitive skills. Non-technical skills are required to be trained and assessed together with knowledge to enhance the patient’s safety and outcome.

scholarly journals UNCERTAIN GROUP DECISION-MAKING WITH INDUCED AGGREGATION OPERATORS AND EUCLIDEAN DISTANCE

2013 ◽  
Vol 19 (3) ◽  
pp. 431-447 ◽  
Author(s):  
Weihua Su ◽  
Shouzhen Zeng ◽  
Xiaojia Ye
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Euclidean Distance ◽  
Group Decision ◽  
Weighted Averaging ◽  
Uncertain Information ◽  
Uncertain Environments ◽  
Interval Numbers ◽  
Ordered Weighted Averaging ◽  
Induced Aggregation

In this paper, we present the induced uncertain Euclidean ordered weighted averaging distance (IUEOWAD) operator. It is an extension of the OWA operator that uses the main characteristics of the induced OWA (IOWA), the Euclidean distance and uncertain information represented by interval numbers. The main advantage of this operator is that it is able to consider complex attitudinal characters of the decision-maker by using order-inducing variables in the aggregation of the Euclidean distance. Moreover, it is able to deal with uncertain environments where the information is very imprecise and can be assessed with interval numbers. We study some of its main properties and particular cases such as the uncertain maximum distance, the uncertain minimum distance, the uncertain normalized Euclidean distance (UNED), the uncertain weighted Euclidean distance (UWED) and the uncertain Euclidean ordered weighted averaging distance (UEOWAD) operator. We also apply this aggregation operator to a group decision-making problem regarding the selection new artillery weapons under uncertainty.

scholarly journals Application of multi-attribute decision-making methods based on normal random variables in supply chain risk management

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Liye Zhang ◽  
Adil Omar Khadidos ◽  
Mohamed Mahgoub
Keyword(s):  
Decision Making ◽  
Mean Square Error ◽  
Weighted Average ◽  
Interval Number ◽  
Mean Square ◽  
Supply Chain Risk Management ◽  
Interval Numbers ◽  
Arithmetic Average ◽  
Weighted Arithmetic ◽  
Optimal Criterion

Abstract For the multi-criteria group decision-making problem where the criterion value is a normal interval number and the weight information is incomplete, the normal interval number and its compromise expected value, compromise mean square error, algorithm, weighted arithmetic average of normal interval number (ININWAA) Operator, the ordered weighted average (ININOWA) operator of normal interval numbers and the mixed weighted average (ININHA) operator of normal interval numbers, and a multi-criteria group with incomplete information based on normal interval numbers is proposed. Decision-making methods. This method uses ININWAA operator and INNHA operator to integrate criterion values, uses the compromise mean square error of criterion values, establishes an optimisation model to solve the optimal criterion weights and uses the expectation variance criterion to determine the order of the schemes. The case analysis shows the effectiveness and feasibility of this method.

Synthesizing Effect Model Based on Quasi-Linear Function in Intelligent Materials System

2011 ◽  
Vol 63-64 ◽  
pp. 29-32
Author(s):  
Shu Xin Luo ◽  
Jing Li ◽  
Fa Chao Li
Keyword(s):  
Decision Making ◽  
Linear Function ◽  
Ranking Method ◽  
Order Structure ◽  
Uncertain Information ◽  
Interval Numbers ◽  
Effect Model ◽  
Wide Range ◽  
Complex Optimization ◽  
Definition Of

Interval number is a common tool to describe uncertain information. Its ranking method plays a role in solving uncertain decision-making problems. In Ref. [1], by analyzing the feature and shortcomings of the current ranking methods, we proposed a ranking method based on quantity property, and systematically discussed the structure criteria, based on it, in this paper, we firstly introduce the definition of quasi-linear function and establishan order model of interval numbers based on it; secondly, with a specific example, we further analysis the property the order structure built in Ref. [1]. The result shows that this method can merge decision making consciousness into the decision making process effectively. In complex optimization system, decision making and other fields have a wide range of applications.

PROBABILISTIC AGGREGATION OPERATORS AND THEIR APPLICATION IN UNCERTAIN MULTI-PERSON DECISION-MAKING / TIKIMYBINIAI SUMAVIMO OPERATORIAI IR JŲ TAIKYMAS PRIIMANT GRUPINIUS SPRENDIMUS NEAPIBRĖŽTOJE APLINKOJE

2011 ◽  
Vol 17 (2) ◽  
pp. 335-351 ◽  
Author(s):  
José M. Merigó ◽  
Guiwu Wei
Keyword(s):  
Decision Making ◽  
Complete Information ◽  
Aggregation Operator ◽  
Weighted Averaging ◽  
Uncertain Information ◽  
Interval Numbers ◽  
Monetary Policies ◽  
Owa Operators ◽  
Probabilistic Information ◽  
Political Management

We present the uncertain probabilistic ordered weighted averaging (UPOWA) operator. It is an aggregation operator that uses probabilities and OWA operators in the same formulation considering the degree of importance of each concept in the analysis. Moreover, it also uses uncertain information assessed with interval numbers in the aggregation process. The main advantage of this aggregation operator is that it is able to use the attitudinal character of the decision maker and the available probabilistic information in an environment where the information is very imprecise and can be assessed with interval numbers. We study some of its main properties and particular cases such as the uncertain probabilistic aggregation (UPA) and the uncertain OWA (UOWA) operator. We also develop an application of the new approach in a multi-person decision-making problem in political management regarding the selection of monetary policies. Thus, we obtain the multiperson UPOWA (MP-UPOWA) operator. We see that this model gives more complete information of the decision problem because it is able to deal with decision making problems under uncertainty and under risk in the same formulation. Santrauka Autoriai pristato tikimybinį svertinio vidurkio operatorių, taikytiną neapibrežtumo sąlygomis. Tai tikimybėmis pagrįstas sumavimo operatorius, kuris kartu su svertinio vidurkio operatoriais gali įvertinti alternatyvų svarbumo laipsnį. Be to, jis gali operuoti neapibrežta informacija, išreikšta skaičiais intervaluose. Pagrindinis šio operatoriaus privalumas yra tas, kad jį galima taikyti uždaviniams, kuriuose informacija yra netiksli. Išnagrinėtos kai kurios minėto operatoriaus savybės. Sukurtas metodas pritaikytas monetarinei politikai parinkti, situacijai, kai sprendimus priima žmoniu grupė. Modelis suteikia išsamesnę informaciją apie problemą, nes gali įvertinti neapibrežtumus ir riziką.

THE UNCERTAIN GENERALIZED OWA OPERATOR AND ITS APPLICATION TO FINANCIAL DECISION MAKING

2011 ◽  
Vol 10 (02) ◽  
pp. 211-230 ◽  
Author(s):  
JOSÉ M. MERIGÓ ◽  
MONTSERRAT CASANOVAS
Keyword(s):  
Decision Making ◽  
Weighted Average ◽  
Uncertain Information ◽  
Owa Operator ◽  
Arithmetic Means ◽  
Interval Numbers ◽  
Wide Range ◽  
Decision Making Problem ◽  
Financial Decision ◽  
Selection Of

We introduce the uncertain generalized OWA (UGOWA) operator. This operator is an extension of the OWA operator that uses generalized means and uncertain information represented as interval numbers. By using UGOWA, it is possible to obtain a wide range of uncertain aggregation operators such as the uncertain average (UA), the uncertain weighted average (UWA), the uncertain OWA (UOWA) operator, the uncertain ordered weighted geometric (UOWG) operator, the uncertain ordered weighted quadratic averaging (UOWQA) operator, the uncertain generalized mean (UGM), and many specialized operators. We study some of its main properties, and we further generalize the UGOWA operator using quasi-arithmetic means. The result is the Quasi-UOWA operator. We end the paper by presenting an application to a decision-making problem regarding the selection of financial strategies.

scholarly journals Venture capital project selection based on interval number grey target decision model

2021 ◽  
Author(s):  
Sha Fu ◽  
Ye-zhi Xiao ◽  
Hang-jun Zhou ◽  
Sheng-zong Liu
Keyword(s):  
Decision Making ◽  
Venture Capital ◽  
Decision Model ◽  
Interval Data ◽  
Interval Number ◽  
Target Distance ◽  
Interval Numbers ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Model

AbstractIn this study, aiming at the multi-attribute decision-making problem with incomplete and uncertain attribute weight information and attribute value of interval numbers, a grey target decision-making model of interval numbers based on positive and negative clouts is proposed. Firstly, in this model, the linear transformation operator of interval number is used to normalize the original decision information, and the positive and negative clouts of interval number are designed. Secondly, after the space projection distance between each scheme and the positive and negative clouts is considered comprehensively, the off-target distance is taken as the basis of vector analysis in space to obtain a new comprehensive off-target distance. The existing interval number grey target decision-making model ignores the important influence of interval distribution and the correlation between the attributes in scheme evaluation, and there are some fuzzy errors when setting the weight of attributes. In order to solve the above problems, this paper combined with the uncertainty analysis of the attribute weights, a goal programming is constructed for the objective function based on the comprehensive off-target distance minimization to solve the attribute weight vector, and finally determine the order of the scheme. Finally, the feasibility and effectiveness of the proposed grey target decision model are verified by an example of venture capital projects. Compared with traditional models, the improved model fully considers the characteristics of interval data and the correlation between the attributes.

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