Fuzzy reliability appraisal of a system using probabilistic dual hesitant fuzzy element emphasising score function

2022 ◽  
Vol 21 (1) ◽  
pp. 67
Author(s):  
Deepak Kumar ◽  
S.B. Singh ◽  
Pawan Kumar
Keyword(s):  
Score Function ◽  
Fuzzy Reliability

Fuzzy Reliability Appraisal Using Interval-Valued Intuitionistic Hesitant Fuzzy Element and Score Function

2021 ◽  
pp. 2140005
Author(s):  
Deepak Kumar ◽  
S. B. Singh
Keyword(s):  
Score Function ◽  
Parallel Structure ◽  
Complex Structures ◽  
Bridge Structure ◽  
Fuzzy Reliability ◽  
Numerical Illustration ◽  
Advanced Technique ◽  
Fuzzy Environment ◽  
Unit Component ◽  
Interval Valued

Here, we appraise the reliability for numerous complex structures (series structure, parallel structure and bridge structure) using accuracy and score function under fuzzy environment. The main focus of this effort is to address an advanced technique for fuzzy reliability evaluation of various complex systems having different arrangements by treating reliability of the unit/component as an interval valued intuitionistic hesitant fuzzy element. This technique helps to handle uncertainty and hesitancy in multi-attribute group decision-making related issues, specially when information occurs in interval form in fuzzy set. A numerical illustration is also included to demonstrate the proposed technique.

Fuzzy System Reliability Using Hesitant Fuzzy Element and Score Function

2021 ◽  
pp. 209-221
Author(s):  
Deepak Kumar ◽  
S. B. Singh ◽  
Anita Kumari
Keyword(s):  
Optimization Problems ◽  
Score Function ◽  
Hesitant Fuzzy Set ◽  
Reliability Engineering ◽  
Fuzzy Reliability ◽  
Fuzzy Environment ◽  
Reliability Modelling ◽  
Series Configuration ◽  
A New Technique ◽  
Parallel Configuration

The present work introduces a new technique for analyzing the fuzzy reliability of a system stem under hesitant fuzzy environment where the reliability of a component/unit of a system is represented by hesitant fuzzy element (HFE). In this study, the authors evaluate the fuzzy reliability for some complex systems (series configuration, parallel configuration, and bridge configuration) using score function which is very useful in reliability modelling (especially in decision making, risk analysis, and optimization problems). Reliability modelling under hesitant situations plays a key role in the reliability engineering field. The score function used in this study is helpful for a simple comparison between reliabilities of any two components as form of HFEs. Hesitancy is the most common problem in human behaviour, for which hesitant fuzzy set can be considered as a useful tool allowing several possible degrees of membership of an element to a set. Additionally, a numerical example is taken for demonstration of the present technique.

scholarly journals Non-Negative Symmetric Low-Rank Representation Graph Regularized Method for Cancer Clustering Based on Score Function

2020 ◽  
Vol 10 ◽  
Author(s):  
Conghai Lu ◽  
Juan Wang ◽  
Jinxing Liu ◽  
Chunhou Zheng ◽  
Xiangzhen Kong ◽  
...  
Keyword(s):  
Score Function ◽  
Low Rank ◽  
Low Rank Representation ◽  
Regularized Method

scholarly journals TransET: Knowledge Graph Embedding with Entity Types

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1407
Author(s):  
Peng Wang ◽  
Jing Zhou ◽  
Yuzhang Liu ◽  
Xingchen Zhou
Keyword(s):  
Link Prediction ◽  
State Of The Art ◽  
Score Function ◽  
Graph Embedding ◽  
Vector Spaces ◽  
Knowledge Graph ◽  
Semantic Features ◽  
Knowledge Graphs ◽  
Real World Datasets ◽  
Low Dimensional

Knowledge graph embedding aims to embed entities and relations into low-dimensional vector spaces. Most existing methods only focus on triple facts in knowledge graphs. In addition, models based on translation or distance measurement cannot fully represent complex relations. As well-constructed prior knowledge, entity types can be employed to learn the representations of entities and relations. In this paper, we propose a novel knowledge graph embedding model named TransET, which takes advantage of entity types to learn more semantic features. More specifically, circle convolution based on the embeddings of entity and entity types is utilized to map head entity and tail entity to type-specific representations, then translation-based score function is used to learn the presentation triples. We evaluated our model on real-world datasets with two benchmark tasks of link prediction and triple classification. Experimental results demonstrate that it outperforms state-of-the-art models in most cases.

scholarly journals The Impact of Mergers and Acquisitions and Sustainability on Company Performance in the Pharmaceutical Sector

2021 ◽  
Vol 13 (12) ◽  
pp. 6525
Author(s):  
Diana Marieta Mihaiu ◽  
Radu-Alexandru Șerban ◽  
Alin Opreana ◽  
Mihai Țichindelean ◽  
Vasile Brătian ◽  
...  
Keyword(s):  
Stock Market ◽  
Mergers And Acquisitions ◽  
Performance Improvement ◽  
Score Function ◽  
Pharmaceutical Companies ◽  
Company Performance ◽  
Direct Impact ◽  
Pharmaceutical Sector ◽  
Financial Measures ◽  
The Impact

The primary goal of this study was to determine the impact of mergers and acquisitions (M&A) and the environmental, social, and governance (ESG) sustainability scores of companies. In this regard, efforts to measure and analyze the evolution of a company’s performance, taking into account financial and non-financial measures using a score function, are adapted to the pharmaceutical sector. The sample consisted of 100 leading pharmaceutical companies, ranked by stock market capitalization, who registered 30% (n = 492) of the total M&A transactions over the study period (2010–2020). There was a direct and positive link between the M&A process and the evolution of company performance. The ESG score, as an indicator for measuring sustainability, has a positive and direct impact on company performance, indicating that a high ESG score determines an increase in company performance. A similar impact is identified for companies involved in M&A processes, meaning that companies in the pharmaceutical sector tend to register a performance improvement.

Complex q-rung orthopair fuzzy Schweizer–Sklar Muirhead mean aggregation operators and their application in multi-criteria decision-making

2021 ◽  
pp. 1-23
Author(s):  
Peide Liu ◽  
Tahir Mahmood ◽  
Zeeshan Ali
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Imaginary Part ◽  
Fuzzy Set ◽  
Score Function ◽  
Aggregation Operators ◽  
Unit Interval ◽  
Multi Criteria Decision Making ◽  
Accuracy Function ◽  
Special Cases

Complex q-rung orthopair fuzzy set (CQROFS) is a proficient technique to describe awkward and complicated information by the truth and falsity grades with a condition that the sum of the q-powers of the real part and imaginary part is in unit interval. Further, Schweizer–Sklar (SS) operations are more flexible to aggregate the information, and the Muirhead mean (MM) operator can examine the interrelationships among the attributes, and it is more proficient and more generalized than many aggregation operators to cope with awkward and inconsistence information in realistic decision issues. The objectives of this manuscript are to explore the SS operators based on CQROFS and to study their score function, accuracy function, and their relationships. Further, based on these operators, some MM operators based on PFS, called complex q-rung orthopair fuzzy MM (CQROFMM) operator, complex q-rung orthopair fuzzy weighted MM (CQROFWMM) operator, and their special cases are presented. Additionally, the multi-criteria decision making (MCDM) approach is developed by using the explored operators based on CQROFS. Finally, the advantages and comparative analysis are also discussed.

Multi-criteria decision-making algorithm based on aggregation operators under the complex interval-valued q-rung orthopair uncertain linguistic information

2021 ◽  
pp. 1-30
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Zaoli Yang ◽  
Tahir Mahmood ◽  
Sultan Aljahdali
Keyword(s):  
Decision Making ◽  
Brain Tumors ◽  
Score Function ◽  
Aggregation Operators ◽  
Multi Criteria Decision Making ◽  
Linguistic Features ◽  
Interval Numbers ◽  
Fundamental Properties ◽  
Interval Valued

The paper aims to present a concept of a Complex interval-valued q-rung orthopair uncertain linguistic set (CIVQROULS) and investigated their properties. In the presented set, the membership grades are considered in terms of the interval numbers under the complex domain while the linguistic features are added to address the uncertainties in the data. To further discuss more, we have presented the operation laws and score function for CIVQROULS. In addition to them, we present some averaging and geometric operators to aggregate the different pairs of the CIVQROULS. Some fundamental properties of the proposed operators are stated. Afterward, an algorithm for solving the decision-making problems is addressed based on the proposed operator using the CIVQROULS features. The applicability of the algorithm is demonstrated through a case study related to brain tumors and their effectiveness is compared with the existing studies.

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