Article
Computer Science, Artificial Intelligence
Wei Jiang, Kai-Qing Zhou, Arezoo Sarkheyli-Hagele, Azlan Mohd Zain
Summary: This paper systematically reviews recent developments of the fuzzy Petri net (FPN) model from the perspectives of knowledge representation, reasoning mechanisms, and industrial applications. The paper also discusses specific modeling and reasoning approaches to solve the 'state-explosion problem' in FPN. Detailed analysis reveals interesting findings and developmental history, concluding with suggestions for future research directions.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Computer Science, Information Systems
Kaiyuan Bai, Dan Jia, Weiye Meng, Xingmin He
Summary: This paper proposes a novel fuzzy Petri nets (FPNs) method based on q-rung orthopair fuzzy sets (q-ROFSs) to handle the uncertain knowledge representation and reasoning efficiently. It introduces q-rung orthopair FPNs (q-ROFPNs) that integrate q-ROFSs with FPNs for intuitive evaluation and flexible adjustment of hesitancy information. The paper also presents a reasoning algorithm based on the ordered weighted averaging-weighted average (OWAWA) operator to accomplish forward reasoning, as well as a decomposition algorithm and an ordered weighted backward reasoning (OWBR) algorithm for backward reasoning in q-rung orthopair fuzzy reversed Petri nets (q-ROFRPNs). The proposed method outperforms the existing FPNs methods in terms of flexibility and reliability in knowledge representation and reasoning.
Review
Computer Science, Artificial Intelligence
Ya-Xuan Yu, Hua-Ping Gong, Hu-Chen Liu, Xun Mou
Summary: Fuzzy Petri nets (FPNs) are a powerful modeling tool for expert systems. This paper conducts a bibliometric analysis of FPN studies to understand the developments, focus areas, and research trends in this field. The analysis reveals that the publication on FPNs has increased rapidly since 2018. The influential authors, emerging research trends, and hot research topics are identified, providing important reference for scholars and practitioners in understanding the research status and future research agenda of FPNs.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Automation & Control Systems
Hu-Chen Liu, Dong-Hui Xu, Chun-Yan Duan, Yun Xiong
Summary: Fuzzy Petri nets (FPNs) are a widely used tool for intelligent decision making, but traditional FPNs struggle with accurately representing uncertain knowledge from domain experts. To address this, Pythagorean FPNs (PFPNs) were developed, incorporating Pythagorean fuzzy sets for capturing imprecise knowledge and a large group truth determination method for assessing truth degrees with massive data. An application example on security risk assessment demonstrates the effectiveness and advantages of PFPNs.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Chemical
Liping Guo, Zhirong Wang
Summary: This paper proposes a research method for multi-level multi-source multi-path multi-order effect based on expert knowledge and fuzzy Petri net model, studies the probability and characteristics of multi-level cascade effects caused by leakage of hazardous substances, and provides a theoretical basis for blocking the evolutionary process of cascade effects.
CHEMICAL ENGINEERING SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Weichao Yue, Lingfeng Hou, Xiaoxue Wan, Xiaofang Chen, Weihua Gui
Summary: Superheat degree is crucial for aluminum electrolysis cell, but current methods have limitations in its recognition. The unbalance double hierarchy linguistic term set (DHLTS) fails to consider the hesitant degree. To address these issues, an unbalance double hierarchy hesitant linguistic Petri net (UDHHLPN) model and extended TOPSIS algorithm are proposed. The model explicitly represents the coupling relationships and introduces relative entropy to enhance the performance of extended TOPSIS. Experimental results show that the proposed method achieves an accuracy of 89.00% for SDRAEC.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Artificial Intelligence
Hu-Chen Liu, Xue Luan, MengChu Zhou, Yun Xiong
Summary: The use of a new type of 2-dimensional uncertain linguistic Petri nets (2DULPN) enables better handling of uncertain linguistic knowledge given by domain experts and their judgments' reliability, as well as capturing the interrelationship among propositions.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Biochemical Research Methods
Fei Liu, Wujie Sun, Monika Heiner, David Gilbert
Summary: The study introduces a method called Fuzzy Continuous Petri Nets for integrated modelling of biological systems, which combines continuous Petri nets with fuzzy inference systems to address uncertainties in the modeling process.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Computer Science, Information Systems
Oz Yakrangi, Roque J. Saltaren Pazmino, Juan S. Cely, Alejandro Rodriguez, Cecilia E. Garcia Cena, Pablo San Segundo Carrillo, Julio De La Cueva, Amir Shapiro
Summary: This article introduces the application of fuzzy Petri net algorithms on the GEMMA guide paradigm, which generates intelligent and safe control of the machine to achieve the best control system. The algorithms are able to make the best decision automatically based on the machine's situation.
Article
Chemistry, Multidisciplinary
Watanee Jearanaiwongkul, Chutiporn Anutariya, Teeradaj Racharak, Frederic Andres
Summary: This study models and encodes knowledge related to rice cultivation using ontologies and semantic technologies, developing an expert system called RiceMan for diagnosing rice field problems. The methodology is evaluated with four groups of stakeholders in Thailand, showing promising results for ontology reasoning in solving domain problems.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Chuanlai Yuan, Yongyi Liao, Lingshuang Kong, Huiqin Xiao
Summary: A novel fault diagnosis method based on TSHFPNs for distribution network is proposed in this paper, which assigns time intervals and introduces Gaussian function to improve the accuracy of fault diagnosis results. The method demonstrates correctness and rationality through comparison and analysis of distribution system examples.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Weichao Yue, Xiao Liu, Sanyi Li, Weihua Gui, Yongfang Xie
Summary: The paper proposes a novel approach to address the challenges in modeling knowledge with fuzziness and uncertainty using FPNs, by introducing the combination of IVIFPNs and ETOPSIS, successfully dealing with cognitive nonconformity and managing fuzziness and uncertainty of expert knowledge.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Biochemical Research Methods
Alexandru Oarga, Bridget P. Bannerman, Jorge Julvez
Summary: Despite the slow pace of new drug production due to high cost and uncertain success, high-throughput technologies and computational methods can be used to identify vulnerabilities in biological models and facilitate novel drug development. However, the current approach only considers topological data, neglecting dynamic information and potentially leading to misidentified drug targets.
Article
Chemistry, Analytical
Michal Markiewicz, Leslaw Gniewek, Dawid Warchol
Summary: This paper introduces a new concept and definition of hierarchical structure for Fuzzy Interpreted Petri Net (FIPN), including the concept of macroplaces and their implementation in a computer simulator called HFIPN-SML.
Article
Engineering, Civil
Gustavo S. da Rocha, Joao Paulo C. Rodrigues, Daniel da Silva Gazzana
Summary: This paper proposes a risk assessment method based on Fuzzy Petri nets to comprehensively evaluate electrical fire risks. The method involves responding to a yes/no questionnaire based on code recommendations to predict the failure mode response. It can evaluate the overall risk, determine the relevance of each electrical issue, and assess the impact of electrical installation improvements on safety.
FIRE SAFETY JOURNAL
(2023)
Article
Operations Research & Management Science
Jia Huang, Hu-Chen Liu, Chun-Yan Duan, Ming-Shun Song
Summary: This paper proposes a new FMEA model to evaluate and prioritize the risk of failure modes by integrating probabilistic linguistic term sets and TODIM method. The probabilistic linguistic term sets handle the ambiguity in risk assessments, while an extended TODIM method determines the priority ranking of failure modes. Additionally, an objective weighting method based on TOPSIS is presented to derive the relative weights of risk factors.
ANNALS OF OPERATIONS RESEARCH
(2022)
Review
Computer Science, Artificial Intelligence
Jian Wang, Qianqian Ma, Hu-Chen Liu
Summary: Meta-evaluation theory and methods were used to evaluate science and technology project review experts, with dozens of criteria identified in two categories. An empirical study was conducted to analyze the relationships among these criteria and propose a method to handle subjective fuzzy data. The proposed model based on IVIF-BWM and MULTIMOORA was applied in a real case study, which demonstrated its accuracy and reliability.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Business
Hu-Chen Liu, Song-Man Wu, Ze-Ling Wang, Xiao-Yang Li
Summary: This paper introduces a novel QFD method integrating EHFLTSs and prospect theory to overcome the limitations of traditional QFD. By using Choquet integral and extended prospect theory, the ranking orders of ECs are determined effectively.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Qiang Li, Qin-Yu Chen, Zheng Liu, Hu-Chen Liu
Summary: This study proposes a new approach for public transport customer satisfaction evaluation based on an extended thermodynamic method with q-rung orthopair fuzzy sets. By utilizing the stepwise weight assessment ratio analysis method to specify the weights of evaluation criteria, the method effectively evaluates the customer satisfaction levels of different rail transit lines in Shanghai.
Article
Computer Science, Artificial Intelligence
Lin Huang, Ling-Xiang Mao, Yao Chen, Hu-Chen Liu
Summary: With the occurrence of various emergency events becoming increasingly frequent, emergency decision making (EDM) has gained significant attention in research. This study proposes a new EDM method that integrates regret theory, evaluation based on distance from average solution (EDAS) method, and 2-tuple spherical linguistic term sets (TSLTSs). The method efficiently ranks and selects the optimal emergency response solution by considering decision makers' uncertain and vague evaluations. The proposed method is applied to a public health emergency in China and is shown to be superior and practical through a comparative analysis with other EDM methods.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Hu-Chen Liu, Xue Luan, MengChu Zhou, Yun Xiong
Summary: The use of a new type of 2-dimensional uncertain linguistic Petri nets (2DULPN) enables better handling of uncertain linguistic knowledge given by domain experts and their judgments' reliability, as well as capturing the interrelationship among propositions.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
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
Green & Sustainable Science & Technology
Hua Shi, Ling-Xiang Mao, Ke Li, Xiang-Hu Wang, Hu-Chen Liu
Summary: A new approach to prioritize engineering characteristics in Quality Function Deployment (QFD) is proposed based on double hierarchy hesitant linguistic term sets and the ORESTE method. This approach overcomes the deficiencies of traditional QFD in handling uncertain assessments and prioritizing engineering characteristics. A case study is presented to illustrate its feasibility and practicability.
Article
Business
Chun-Yan Duan, Xu-Qi Chen, Hua Shi, Hu-Chen Liu
Summary: Failure mode and effects analysis (FMEA) is a tool used to improve the reliability and safety of a system, process, or service. However, traditional FMEA has limitations that affect its effectiveness. This article proposes a new FMEA model using double hierarchy hesitant fuzzy linguistic term sets and k-means clustering to evaluate and cluster the risk of failure modes. A case study is presented to demonstrate the effectiveness and usefulness of this approach.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Review
Computer Science, Artificial Intelligence
Ya-Xuan Yu, Hua-Ping Gong, Hu-Chen Liu, Xun Mou
Summary: Fuzzy Petri nets (FPNs) are a powerful modeling tool for expert systems. This paper conducts a bibliometric analysis of FPN studies to understand the developments, focus areas, and research trends in this field. The analysis reveals that the publication on FPNs has increased rapidly since 2018. The influential authors, emerging research trends, and hot research topics are identified, providing important reference for scholars and practitioners in understanding the research status and future research agenda of FPNs.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Engineering, Industrial
Hu -Chen Liu, Jing-Hui Wang, Ling Zhang, Qi-Zhen Zhang
Summary: Human reliability analysis is a method used to enhance the safety and reliability of complex socio-technical systems. Current studies often involve small groups of experts, which is insufficient for addressing increasingly complex problems. This article proposes a large group SLIM model that considers experts' noncooperative behaviors and social relations, and effectively calculates the human error probabilities of tasks.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Automation & Control Systems
Hua Shi, Jing-Hui Wang, Ling Zhang, Hu-Chen Liu
Summary: Because human errors are the main cause of accidents in safety-critical industries, human reliability analysis (HRA) is crucial for improving the reliability of complex engineering systems. However, assessing human errors is challenging due to uncertainty in state evaluation information, multiple common performance conditions (CPCs), and their correlations. This paper proposes a new cognitive reliability and error analysis method (CREAM) that integrates linguistic D numbers and the decision-making trial and evaluation laboratory-based analytic network process (DANP) method to quantitatively analyze human errors.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Zheng Liu, Xun Mou, Hu-Chen Liu, Ling Zhang
Summary: This article presents a new FMEA approach that integrates probabilistic linguistic preference relations (PLPRs) and gained and lost dominance score (GLDS) method. The PLPRs are used to describe risk evaluations of experts through pairwise comparison of failure modes. An extended GLDS method is introduced to consider both group and individual risk attitudes and determine the risk ranking of failure modes. Furthermore, a two-step optimization model is proposed to determine the weights of risk factors when their weighing information is unknown.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Ya-Juan Han, Miao-Miao Cao, Hu-Chen Liu
Summary: This paper proposes a new hybrid QFD approach for determining the priority of engineering characteristics in order to satisfy customer requirements. It utilizes multi-granular unbalanced linguistic term sets to describe vague relational evaluations and employs an opinion evolution social network consensus reaching model to derive consensual relational evaluations. The combined compromise solution method is adopted to determine the priority orders of engineering characteristics, taking into account conflicting customer requirements.
APPLIED SOFT COMPUTING
(2023)
Article
Psychology, Multidisciplinary
Wei Guo, Xin-Rong Chen, Hu-Chen Liu
Summary: Research shows that Easterners are more risk intolerant but more willing to accept ambiguous conditions in the gain domain compared to Westerners. Surprisingly, Easterners and Westerners have similar attitudes towards risk and ambiguity in the loss domain. Cultural differences between Western and Eastern countries may explain the higher level of risk aversion observed among East Asians.
BEHAVIORAL SCIENCES
(2022)
