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Article
Computer Science, Artificial Intelligence
Shifan He et al.
Summary: This paper focuses on the evaluation of new energy vehicles (NEVs) through online reviews. Online reviews are collected using data crawling technology and a data-driven method is used to extract attributes and conduct sentiment analysis. A new information transformation mechanism is proposed to convert unstructured data into picture fuzzy numbers. Weight determination and regret theory are also applied for attribute weighting and quantifying consumer behavior. A case study and discussions are provided to demonstrate the implementation and superiority of the proposed evaluation method.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Ghous Ali et al.
Summary: The study introduces a novel hybrid model called interval-valued q-rung orthopair fuzzy soft sets, explores its basic properties and attribute reduction techniques, and validates the effectiveness of reduction methods through a numerical example.
APPLIED INTELLIGENCE
(2022)
Article
Multidisciplinary Sciences
Chittaranjan Shit et al.
Summary: This article introduces a method utilizing picture fuzzy sets to handle problems with uncertainty and vagueness, and develops three harmonic mean operators. By studying the related properties of these operators and comparing their applications in a multi-attribute decision-making problem, the effectiveness of these operators is demonstrated.
Article
Computer Science, Artificial Intelligence
Yuan Rong et al.
Summary: Emergency schemes assessment is a crucial activity for improving emergency management, involving multiple attribute decision making. This paper proposes an innovative decision algorithm that considers the prioritized relations and correlation of attributes, utilizing picture fuzzy numbers, Archimedean copula, and prioritized operators to design various operators for fusing picture fuzzy assessment data. This novel methodology is applied to real-life emergency management scheme assessment, demonstrating superior efficiency through numerical and comparative analysis.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Zhe Wang et al.
Summary: This paper proposes a novel Interval-Valued Intuitionistic Fuzzy Jenson-Shannon (IVIFJS) divergence to measure the difference between Interval-Valued Intuitionistic Fuzzy Sets (IVIFSs). A new Evaluation Score Function for IVIFS is also proposed, which is flexible and enclosed in a fixed interval. The proposed divergence operator and MADM method are evaluated through numerical examples, showing their applicability and stability.
APPLIED INTELLIGENCE
(2022)
Article
Automation & Control Systems
Elif Haktanir et al.
Summary: This paper presents a new integrated CRITIC and REGIME methodology that uses picture fuzzy sets to handle ambiguity and impreciseness. The methodology produces effective and valid results in the selection problem.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Information Systems
Dejian Yu et al.
Summary: This paper systematically analyzes the thematic evolution and knowledge diffusion paths in the field of intuitionistic fuzzy set theory through the analysis of thousands of papers. Five important thematic areas are identified, with MCDM/MADM-GDM being the most important topic. The research topics have shifted from theoretical construction to practical application, and various factors influencing the main path results are discussed.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Zhe Wang et al.
Summary: This paper proposes a new entropy measure for Pythagorean fuzzy sets (PFS) by considering both fuzziness entropy and hesitation entropy. The proposed measure is compared with existing methods and its superiority is illustrated through experiments.
Article
Social Issues
Mahyar Kamali Saraji et al.
Summary: To address environmental and climate change challenges, the circular economy has gained worldwide attention. Manufacturing sectors play a crucial role in improving living standards but are associated with unsustainable production and consumption patterns. This study aims to assess manufacturing sectors' circular supply chain management indicators using a novel fuzzy framework.
TECHNOLOGY IN SOCIETY
(2022)
Article
Multidisciplinary Sciences
Ghous Ali et al.
Summary: This paper proposes a novel hybrid model called spherical fuzzy bipolar soft sets (SFBSSs) to handle real-world decision-making problems regarding falling economies, power crises, etc. By combining spherical fuzzy sets and bipolar soft sets and considering the symmetry of opposite parameters, the proposed model can symmetrically deal with information in a bipolar soft environment. The paper provides a detailed illustration of the model and discusses its properties and algebraic operations. Furthermore, the model is applied to a decision-making problem concerning the ranking of fish passage designs for a hydroelectric project, demonstrating its effectiveness.
Article
Computer Science, Artificial Intelligence
Muhammad Akram et al.
Summary: This article introduces the application of q-rung picture fuzzy sets and Einstein operators, and proposes new q-rung picture fuzzy aggregation operators by combining them. The application of these operators in multi-attribute decision-making is discussed. An algorithm for solving complex decision-making problems using these operators is developed. The practicality and superiority of the proposed method are demonstrated through two practical case studies.
GRANULAR COMPUTING
(2022)
Article
Mathematical & Computational Biology
Muhammad Akram et al.
Summary: This paper introduces a new decision-making framework model, called 2-tuple linguistic complex q-rung picture fuzzy sets (2TLCq-RPFSs), and proposes corresponding aggregation operators. This model helps better represent two-dimensional information and plays an important role in multi-attribute decision making.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Ghous Ali et al.
Summary: Fermatean fuzzy set theory is a novel mathematical tool for handling uncertainties in different real-world domains, presenting a more flexible and reliable approach compared to intuitionistic and Pythagorean fuzzy sets. This paper introduces a new hybrid model, the Fermatean fuzzy bipolar soft set, which extends existing models and explores applications in various decision-making scenarios, such as selecting a surgeon robot and analyzing the impact of COVID-19.
GRANULAR COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Muhammad Akram et al.
Summary: This paper redesigns the Dijkstra algorithm to handle uncertain network parameters by allowing them to take the form of special picture fuzzy numbers. It defines and compares trapezoidal picture fuzzy numbers, proposes an adapted form of the Dijkstra algorithm for picture fuzzy shortest path problems, and numerically evaluates its practicality on a transmission network. Finally, it presents a comparative analysis with the fuzzy Dijkstra algorithm to support the proposed method's validity.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Mathematics, Applied
Ubaid Ur Rehman et al.
Summary: This article introduces the concept of picture fuzzy N-soft sets, incorporating the concept of neutral grade into fuzzy set theory. The fundamental properties of PFN-SS are defined, including M-subset, F-subset, compliment, intersections, and unions. An algorithm for coping with PFN-SS data is proposed, showing its generality and usefulness compared to existing methods such as IFN-SS, FN-SS, and N-SS.
FUZZY INFORMATION AND ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Vladimir Simic et al.
Summary: This study examines how to determine the best location for a vehicle shredding facility under complex criteria using a novel picture fuzzy CODAS method. Results showed Bor as the optimal choice among alternatives, and comparative and sensitivity analyses demonstrated the method's robustness. The proposed method helps waste managers make decisions effectively and efficiently.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Abdul Haseeb Ganie et al.
Summary: This study introduces a novel picture fuzzy (PF) similarity measure for modeling fuzzy sets and for multi-attribute decision-making, which overcomes some drawbacks of existing methods.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Abdul Haseeb Ganie et al.
Summary: The study introduces a novel picture fuzzy distance measure based on direct operations on membership functions, and discusses its advantages in pattern classification problems. Conversion formulae are derived to apply the proposed method in real data sets. Additionally, a new multi-attribute decision-making method using the proposed PF distance measure is introduced and its performance is compared with classical methods in a PF environment.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Review
Construction & Building Technology
Song-Shun Lin et al.
Summary: This paper provides a brief review and bibliometric analysis of major accidents and risk assessment methods for excavation system in recent years. The study highlights the importance of summarizing potential risks during excavation for establishing an early warning system. It also presents the applications of fuzzy set theory and machine learning methods in risk assessment, along with a case study demonstrating the use of machine learning for risk evaluation in excavation. Moreover, the integration of 3S techniques and sensors into building information modelling platform shows promising perspectives for dynamic safety risk monitoring, control, and management.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Multidisciplinary Sciences
Muhammad Shoaib et al.
Summary: Fuzzy graphs (FGs) can be used in natural and human-made structures to study uncertain and inconsistent information. By introducing new definitions and results for the picture of the fuzzy graph (PFG), limitations of FGs can be reduced. This study also explores the application of PFGs in digital marketing and social networking.
Article
Automation & Control Systems
M. Sarwar Sindhu et al.
Summary: This study introduces bipolar picture fuzzy sets (BP(c)FSs) and develops aggregation operators and a multiple criteria decision-making approach to deal with vague data, demonstrating the authenticity and efficacy of the proposed method through examples and analysis.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Muhammad Akram et al.
Summary: The q-rung picture fuzzy VIKOR and TOPSIS techniques proposed in this study are innovative and improved versions that utilize multiple advantages to obtain compromise results and rankings of alternatives in decision-making problems. This methodology calculates the normal weights of attributes using entropy weighting information and creates a compromise solution that is applicable for maximum group utility and minimum individual regret.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Physics, Multidisciplinary
Fairouz Tchier et al.
Summary: A novel hybrid model called picture fuzzy soft expert sets is proposed in this study by combining picture fuzzy sets with soft expert sets, aiming to deal with uncertainties in different decision-making problems. The model can be viewed as a more generalized form of intuitionistic fuzzy soft expert sets, with some novel desirable properties.
Article
Computer Science, Artificial Intelligence
Tahir Mahmood et al.
Summary: The study introduces the concept of complex picture fuzzy N-soft sets (CPFN-SS) to handle complex data and uncertainties in decision-making. By generalizing various fuzzy set concepts, basic operations and algorithms on CPFN-SS are demonstrated, showcasing its advantages and utility in real-world applications.
Article
Mathematics
Ghous Ali et al.
Summary: The study introduces a new q-rung orthopair fuzzy bipolar soft set model, which is capable of handling multi-attribute decision-making and has been successfully tested for various operations. It also explores the model's application in two real-life scenarios and compares it with existing models.
Article
Computer Science, Artificial Intelligence
Muhammad Akram et al.
Summary: This article presents two novel hybrid multi-attribute decision-making models to handle multipolar information under fuzziness. The proposed concepts are illustrated with examples and efficient algorithms are developed to solve the problems. The comparison analysis of the proposed approaches with existing models is also discussed.
GRANULAR COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Azmat Hussain et al.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Abdul Haseeb Ganie et al.
NEURAL COMPUTING & APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Nosheen Malik et al.
Article
Green & Sustainable Science & Technology
Le Wang et al.
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Multidisciplinary Sciences
Li Li et al.
Article
Computer Science, Artificial Intelligence
Yong Yang et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2015)
Article
Computer Science, Artificial Intelligence
Pushpinder Singh
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
Bui Cong Cuong et al.
2015 SEVENTH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE)
(2015)
Article
Computer Science, Artificial Intelligence
Munazza Naz et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2014)
Article
Mathematics, Applied
M. Irfan Ali et al.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2009)
Article
Mathematics, Applied
A. R. Roy et al.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2007)
