001481037 000__ 05554cam\\22005657a\4500
001481037 001__ 1481037
001481037 003__ OCoLC
001481037 005__ 20231031003320.0
001481037 006__ m\\\\\o\\d\\\\\\\\
001481037 007__ cr\un\nnnunnun
001481037 008__ 230923s2023\\\\si\\\\\\o\\\\\000\0\eng\d
001481037 019__ $$a1398462979
001481037 020__ $$a9789819951543$$q(electronic bk.)
001481037 020__ $$a9819951542$$q(electronic bk.)
001481037 020__ $$z9819951534
001481037 020__ $$z9789819951536
001481037 0247_ $$a10.1007/978-981-99-5154-3$$2doi
001481037 035__ $$aSP(OCoLC)1399167342
001481037 040__ $$aEBLCP$$beng$$cEBLCP$$dYDX$$dGW5XE$$dEBLCP$$dOCLCO
001481037 049__ $$aISEA
001481037 050_4 $$aQA267
001481037 08204 $$a511.35$$223/eng/20230928
001481037 1001_ $$aShi, Hua.
001481037 24510 $$aFuzzy petri nets for knowledge representation, acquisition and reasoning /$$cHua Shi, Hu-Chen Liu.
001481037 260__ $$aSingapore :$$bSpringer,$$c2023.
001481037 300__ $$a1 online resource (476 p.)
001481037 500__ $$a6.3.2 PFPN Representations of WPFPRs
001481037 5050_ $$aIntro -- Preface -- Contents -- Abbreviations -- List of Figures -- List of Tables -- Part I Literature Review and Truth Determination of FPNs -- 1 FPNs for Knowledge Representation and Reasoning: A Literature Review -- 1.1 Introduction -- 1.2 FPRs and FPNs -- 1.2.1 FPRs -- 1.2.2 FPNs -- 1.3 Improvements of FPNs -- 1.3.1 Reasoning Algorithms -- 1.3.2 New FPN Models -- 1.4 Applications of FPNs -- 1.4.1 Operational Management -- 1.4.2 Fault Diagnosis and Risk Assessment -- 1.4.3 Wireless Sensor Networks -- 1.4.4 Transportation Systems -- 1.4.5 Biological and Healthcare Systems
001481037 5058_ $$a1.4.6 Other Applications -- 1.5 Observations and Findings -- 1.6 Chapter Summary -- References -- 2 FPNs for Knowledge Representation and Reasoning: A Bibliometric Analysis -- 2.1 Introduction -- 2.2 Research Methodology -- 2.3 Results and Discussions -- 2.3.1 Publication Trend in the FPN Field -- 2.3.2 Cooperation Network Analysis in the FPN Field -- 2.3.3 Co-Citation Analysis in the FPN Field -- 2.3.4 Keyword Analysis in the FPN Field -- 2.3.5 Application Field Analysis -- 2.4 Suggestions for Future Research -- 2.5 Chapter Summary -- References
001481037 5058_ $$a3 Determining Truth Degrees of Input Places in FPNs -- 3.1 Introduction -- 3.2 Preliminaries -- 3.2.1 Hesitant 2-Tuple Linguistic Term Sets -- 3.2.2 Interval 2-Tuple Linguistic Model -- 3.3 The Proposed Model -- 3.3.1 Assess the Truth Degrees of Input Places -- 3.3.2 Determine the Weight Vector of Experts -- 3.3.3 Compute the Truth Values of Input Places -- 3.4 Illustrative Example -- 3.5 Chapter Summary -- References -- Part II Improved FPNs for Knowledge Representation and Acquisition -- 4 Dynamic Adaptive Fuzzy Petri Nets for Knowledge Representation and Acquisition -- 4.1 Introduction
001481037 5058_ $$a4.2 Fuzzy Evidential Reasoning Approach -- 4.2.1 Acquisition of Rule-Based Knowledge Using Belief Structures -- 4.2.2 Group Belief Structures -- 4.2.3 Defuzzification -- 4.3 Dynamic Adaptive Fuzzy Petri Nets -- 4.3.1 Definition of DAFPNs -- 4.3.2 DAFPN Representations for WFPRs -- 4.3.3 Execution Rules of DAFPNs -- 4.3.4 Concurrent Reasoning Algorithm of DAFPNs -- 4.4 An Illustrative Example -- 4.5 Chapter Summary -- References -- 5 Interval-Valued Intuitionistic FPNs for Knowledge Representation and Acquisition -- 5.1 Introduction -- 5.2 Interval 2-Tuple Linguistic Variables
001481037 5058_ $$a5.3 Interval-Valued Intuitionistic Fuzzy Petri Nets -- 5.3.1 Definition of IVIFPNs -- 5.3.2 Representations of IVIFPRs -- 5.3.3 Inference Algorithm of IVIFPNs -- 5.4 The Proposed KRA Model -- 5.5 Empirical Case Study -- 5.5.1 Background -- 5.5.2 Knowledge Acquisition -- 5.5.3 Knowledge Representation and Reasoning -- 5.6 Chapter Summary -- References -- 6 Picture Fuzzy Petri Nets for Knowledge Representation and Acquisition -- 6.1 Introduction -- 6.2 Preliminaries -- 6.2.1 Picture Fuzzy Sets -- 6.2.2 Defuzzification of PFNs -- 6.3 Picture Fuzzy Petri Nets -- 6.3.1 Definition of PFPNs
001481037 506__ $$aAccess limited to authorized users.
001481037 520__ $$aThis book provides valuable knowledge, useful fuzzy Petri nets (FPN) models, and practical examples that can be considered by mangers in supporting knowledge management of organizations to increase and sustain their competitive advantages. In this book, the authors proposed various improved FPN models to enhance the modeling power and applicability of FPNs in knowledge representation and reasoning. This book is useful for practitioners and researchers working in the fields of knowledge management, operation management, information science, industrial engineering, and management science. It can also be used as a textbook for postgraduate and senior undergraduate students.
001481037 588__ $$aDescription based on print version record.
001481037 650_6 $$aRéseaux de Pétri flous.
001481037 650_6 $$aGestion des connaissances$$xMathématiques.
001481037 650_0 $$aFuzzy Petri nets.
001481037 650_0 $$aKnowledge management$$xMathematics.$$vCongresses$$0(DLC)sh2008106316
001481037 655_0 $$aElectronic books.
001481037 7001_ $$aLiu, Hu-Chen.
001481037 77608 $$iPrint version:$$aShi, Hua$$tFuzzy Petri Nets for Knowledge Representation, Acquisition and Reasoning$$dSingapore : Springer Singapore Pte. Limited,c2023$$z9789819951536
001481037 852__ $$bebk
001481037 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5154-3$$zOnline Access$$91397441.1
001481037 909CO $$ooai:library.usi.edu:1481037$$pGLOBAL_SET
001481037 980__ $$aBIB
001481037 980__ $$aEBOOK
001481037 982__ $$aEbook
001481037 983__ $$aOnline
001481037 994__ $$a92$$bISE