Article
Computer Science, Artificial Intelligence
Wen Jiang, Yuanna Liu, Xinyang Deng
Summary: Entity alignment is the process of associating semantically identical entities in different knowledge graphs. The proposed fuzzy entity alignment method FuzzyEA utilizes embeddings to align entities, iteratively learns knowledge graph structure, and fuses alignment results from multiple embeddings to enhance accuracy and discrimination ability. Experiments show that FuzzyEA consistently outperforms other entity alignment methods in terms of alignment accuracy and discrimination ability.
Article
Computer Science, Artificial Intelligence
Li Li, Yongfang Xie, Xiaofang Chen
Summary: Root cause diagnosis is crucial for efficient decision-making in industrial production processes. A dynamic uncertain causality graph model (DUCG) based on picture fuzzy set (PFS) is proposed to address the problem of uncertain knowledge representation and reasoning. The enhanced knowledge reasoning algorithm based on PFS operators proves to be more reliable and flexible in resolving causal inference problems.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Yu-Jie Zhu, Wei Guo, Hu-Chen Liu
Summary: This article proposes a new type of DUCG model by integrating PULSs and the EDAS method, which can overcome the shortcomings of the traditional model and provide more accurate representation of expert knowledge, as well as handling conflicting opinions among experts.
APPLIED SCIENCES-BASEL
(2022)
Article
Multidisciplinary Sciences
Rashad Ismail, Sami Ullah Khan, Samer Al Ghour, Esmail Hassan Abdullatif Al-Sabri, Maha Mohammed Saeed Mohammed, Shoukat Hussain, Fiaz Hussain, Giorgio Nordo, Arif Mehmood
Summary: The notion of fuzzy graph is widely used in various fields. This paper investigates the graph of picture fuzzy set and introduces the concepts of domination theory and double domination theory. The choice of fuzzification and defuzzification methods depends on the specific application and fuzzy set type being used.
Article
Computer Science, Hardware & Architecture
Guoming Lu, Hao Zhang, Ke Qin, Kai Du
Summary: Recently, there has been extensive research on reasoning methodologies for uncertain knowledge graphs, but symbolic reasoning for uncertain knowledge graphs is lacking. This paper introduces a causal-based symbolic reasoning framework called UKGCSR, which utilizes multi-hop reasoning and causal inference to infer object entity and triple confidence. The multi-hop reasoning module treats the reasoning process as a Markov decision process and explores paths and reliability between entities. The causal inference module constructs a causal diagram and generates counterfactuals to evaluate each path's contribution to the triple, thus calculating the confidence of prediction facts. Our model offers interpretability during the reasoning process and demonstrates promising performance in experimental results.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
E. Fathy
Summary: Uncertainty linear programming (ULP) has been a significant subject of study and interest in recent decades. This paper focuses on the ULP problem where all parameters and/or decision variables are expressed as interval-valued intuitionistic fuzzy (IVIF) numbers. Two methods, IVIFLP and FIVIFLP, are proposed to solve the LP problem with IVIF parameters and variables. The methods involve reducing the problems into smaller crisp linear problems (CLPs) and applying reduction techniques based on linear combinations between variables. The proposed methods are illustrated numerically and demonstrate improvements over existing methods for solving transportation problems in an IVIF environment.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, Jie Tang
Summary: CogKR is a framework that conducts multi-hop reasoning by traversing the knowledge graph, and it can handle complex reasoning scenarios. Experimental results show that CogKR outperforms existing methods in terms of accuracy and scalability.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Mathematics
Shahzad Faizi, Heorhii Svitenko, Tabasam Rashid, Sohail Zafar, Wojciech Salabun
Summary: This paper proposes operations and properties on the cubic intuitionistic set, including the internal and external cubic intuitionistic sets, P-order, R-order, P-union, R-union, P-intersection, and R-intersection. The paper investigates properties of these operations and presents examples. Important theorems related to the internal and external cubic intuitionistic sets are also presented. The effectiveness and significance of the proposed operations are measured through solving a multi-criteria decision-making problem.
Article
Computer Science, Information Systems
Shahzaib Ashraf, Wania Iqbal, Shakoor Ahmad, Faisal Khan
Summary: This study aims to highlight circular spherical fuzzy sets as an effective method for dealing with data ambiguity, and proposes novel operators for multiple attribute decision-making.
Article
Mathematics
Lilija Atanassova, Piotr Dworniczak
Summary: This study introduces a new operation increment over intuitionistic fuzzy sets and explores its properties, including analogues to De Morgan's Law, the Fixed Point Theorem, and connections to classical modal operators over IFS Necessity and Possibility. The operation increment can be used for de-fuzzification, and a geometrical interpretation of the construction process is provided.
Article
Computer Science, Information Systems
Pu Li, Xin Wang, Hui Liang, Suzhi Zhang, Yazhou Zhang, Yuncheng Jiang, Yong Tang
Summary: This paper presents a new semantic representation and reasoning model for multiple associative predicates based on fuzzy theory to address the issue of ineffective representation of fuzzy semantic information in classical knowledge graphs. Experimental results demonstrate that the proposed method can discover more implicit valid knowledge with fuzzy semantics and is consistent with human judgments.
INFORMATION SCIENCES
(2022)
Article
Mathematics, Applied
Nazia Nazir, Tanzeela Shaheen, LeSheng Jin, Tapan Senapati
Summary: A dominating vertex set is a subset of vertices in a graph that either includes every vertex or has adjacent vertices. Dominating vertex sets are important in graph theory for understanding graph behavior and optimization problems. This paper proposes a new algorithm for finding dominating vertex sets in fuzzy graphs, addressing limitations of existing methods and improving efficiency.
Article
Mathematics, Applied
Atiqe Ur Rahman, Muhammad Saeed, Hamiden Abd El-Wahed Khalifa, Walaa Abdullah Afifi
Summary: This study generalizes the concept of possibility intuitionistic fuzzy hypersoft set and proposes algorithms based on AND/OR operations for decision making. The set-theoretic operations and similarity measure of possibility intuitionistic fuzzy hypersoft sets are investigated with numerical examples, matrix and graphical representations. The proposed structure and similarity formulation are compared with existing models to validate their effectiveness.
Article
Mathematics, Applied
Chunfeng Suo, Yan Wang, Dan Mou
Summary: This study presents a new axiomatic definition of knowledge measures for intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets. The characteristics of the suggested knowledge measure are analyzed based on mathematical analysis and numerical examples.
Article
Computer Science, Artificial Intelligence
Qin Zhang, Xusong Bu, Mingxia Zhang, Zhan Zhang, Jie Hu
Summary: This paper extends the Dynamic Uncertain Causality Graph (DUCG) for better application in general clinical diagnoses, introducing special logic gates, reversal logic gates, disease-specific manifestation variables, and event attention importance. Through a case study on 25 diseases causing nasal obstruction, the extended DUCG achieved a diagnosis precision of 100%. The third-party verification performed by Suining Central Hospital showed a diagnosis precision of 98.86%, indicating the strong generalization ability of the extended DUCG.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)