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Fuzzy Sets in Business Management, Finance, and Economics
| Fuzzy Sets in Business Management, Finance, and Economics |
| Autore | de Andres Sanchez Jorge |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (346 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
Bonferroni means
prioritized aggregation operators induced aggregation operators OWA operator transparency fuzzy sets fuzzy numbers linguistic variables fuzzy data analysis correlation between fuzzy variables poverty policy efficiency Debreu–Farrell productivity index cryptocurrencies bitcoin blockchain fintech unified theory of acceptance and use of technology intention to use fuzzy set qualitative comparative analysis bonus-malus system fuzzy number fuzzy transition probability fuzzy Markov chain fuzzy stationary state SDGs The Quintuple Helix of Innovation Model sustainability Latin America knowledge systems Forgotten Effects Theory Fuzzy Logic tourist destination competitiveness experton theory forgotten effects theory Hamming distance decision making expert group neuro-fuzzy assessment evaluation of specialists smart city assessment risk smart transport mobility transparent selection public financial resources recovery plan selection of quality methods manufacturing process intuitionistic fuzzy sets genetic algorithm adoption of environmental practices human resource costs organizational learning capability information technology support size education level experience university ranking unsupervised pattern recognition clustering techniques corruption perception corruption normalization gender entrepreneurial intention STEM family entrepreneurial background fsQCA household income pythagorean membership financial knowledge decision-making fuzzy logic fuzzy arithmetic extension principle economic models Harrod’s growth enhancement strategy brand attachment convenience stores fuzzy quality function deployment audit team leader audit risk assessment small- and medium-sized audit firms planification fuzzy theory |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557612703321 |
de Andres Sanchez Jorge
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fuzzy Sets, Fuzzy Logic and Their Applications 2020
| Fuzzy Sets, Fuzzy Logic and Their Applications 2020 |
| Autore | Voskoglou Michael |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (452 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
bipolar gradation of openness
bipolar gradation of closedness bipolar fuzzy topology bipolar gradation preserving map fuzzy collaborative forecasting dynamic random access memory partial consensus fuzzy intersection fuzzy linear system fuzzy number fuzzy number vector embedding method inductive and deductive reasoning fuzzy logic (FL) scientific method probability and statistics Bayesian probabilities fuzzy implication ordering property least fuzzy negation t-conditionality neutrosophic set plithogenic set fuzzy set entropy similarity measure information measure Hyers-Ulam stability pexider type functional equation intuitionistic fuzzy normed spaces alternative fixed point theorem interval-valued fuzzy competition graph interval-valued fuzzy p competition graph interval-valued fuzzy neighbourhood graph interval-valued m-step fuzzy competition graph homomorphism of graph products max-min algebra fuzzy max-T algebra Łukasiewicz triangular norm max-Łukasiewicz algebra parametric solvability soft set fuzzy soft set multi-fuzzy set multi-fuzzy soft set ℒℳℱ?? similarity measure of ℒℳℱ?? site selection shopping mall site selection linguistic terms for fuzzy variable fuzzy AHP fuzzy TOPSIS octahedron set i-octahedron subgroupoid i-octahedron ideal i-sup-property, i-octahedron subgroup i-octahedron subring interval matrix interval eigenvector strong interval eigenvector fuzzy nonlinear systems fuzzy arithmetic fuzzy calculus multidimensional fuzzy arithmetic RDM fuzzy arithmetic fuzzy parametric form fuzzy measures monotone measures product spaces Schauder fixed point theorem fuzzy normed linear space t-norm measure of non-compactness fuzzy logic connectives law of importation α-migrativity distance measure fuzzy differential equations fuzzy difference equations mixed continuous-discrete model strongly generalized Hukuhara differentiability time value of money GEFS SEFS fuzzy relations: fuzzy sets max–min composition min–max composition monotone statistical parameters fuzzy statistics FAHP FTOPSIS FCOPRAS hexagonal fuzzy number governance fuzzy logic management system type-2 fuzzy set fuzzification type-reduction defuzzification B-spline surface model function |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557343903321 |
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Voskoglou Michael
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Theory and Applications of Ordered Fuzzy Numbers [[electronic resource] ] : A Tribute to Professor Witold Kosiński / / edited by Piotr Prokopowicz, Jacek Czerniak, Dariusz Mikołajewski, Łukasz Apiecionek, Dominik Ślȩzak
| Theory and Applications of Ordered Fuzzy Numbers [[electronic resource] ] : A Tribute to Professor Witold Kosiński / / edited by Piotr Prokopowicz, Jacek Czerniak, Dariusz Mikołajewski, Łukasz Apiecionek, Dominik Ślȩzak |
| Autore | Łukasz Apiecionek |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Springer Nature, 2017 |
| Descrizione fisica | 1 online resource (XVIII, 322 p. 156 illus., 106 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Studies in Fuzziness and Soft Computing |
| Soggetto topico |
Computational intelligence
Control engineering Operations research Decision making Management science Computational Intelligence Control and Systems Theory Operations Research/Decision Theory Operations Research, Management Science |
| Soggetto non controllato |
fuzzy prediction models
uncertainty modeling trend processing propagation of uncertainty fuzzy arithmetic analysis defuzzyfication Kosinski’s fuzzy numbers |
| ISBN | 3-319-59614-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Memories of Professor Witold Kosiński -- Scientific Development -- Scientific and Academic Achievements (Part I) -- Scientific and Academic Achievements (Part II) -- Scientific Collaboration -- Teaching and Supervision -- Scientific and Social Services -- Personality and Memoires -- Acknowledgements -- Contents -- Part I Background of Fuzzy Set Theory -- 1 Introduction to Fuzzy Sets -- 1.1 Classic and Fuzzy Sets -- 1.2 Fuzzy Sets---Basic Definitions -- 1.3 Extension Principle -- 1.4 Fuzzy Relations -- 1.5 Cylindrical Extension and Projection of a Fuzzy Set -- 1.6 Fuzzy Numbers -- 1.7 Summary -- References -- 2 Introduction to Fuzzy Systems -- 2.1 Introduction -- 2.2 Fuzzy Conditional Rules -- 2.3 Approximate Reasoning -- 2.3.1 Compositional Rule of Inference -- 2.3.2 Approximate Reasoning with Knowledge Base -- 2.3.3 Fuzzification and Defuzzification -- 2.4 Basic Types of Fuzzy Systems -- 2.4.1 Mamdani--Assilan Fuzzy Model -- 2.4.2 Takagi--Sugeno--Kang Fuzzy System -- 2.4.3 Tsukamoto Fuzzy System -- 2.5 Summary -- References -- Part II Theory of Ordered Fuzzy Numbers -- 3 Ordered Fuzzy Numbers: Sources and Intuitions -- 3.1 Introduction -- 3.2 Problems with Calculations on Fuzzy Numbers -- 3.3 Related Work -- 3.4 Decomposition of Fuzzy Memberships -- 3.5 Idea of Ordered Fuzzy Numbers -- 3.6 Summary -- References -- 4 Ordered Fuzzy Numbers: Definitions and Operations -- 4.1 Introduction -- 4.2 The Ordered Fuzzy Number Model -- 4.3 Basic Notions for OFNs -- 4.3.1 Standard Representation of OFNs -- 4.3.2 OFN Support -- 4.3.3 OFN Membership Function -- 4.3.4 Real Numbers as OFN Singletons -- 4.4 Improper OFNs -- 4.5 Basic Operations on OFNs -- 4.5.1 Addition and Subtraction -- 4.5.2 Multiplication and Division -- 4.5.3 General Model of Operations -- 4.5.4 Solving Equations -- 4.6 Interpretations of OFNs.
4.6.1 Direction as a Trend -- 4.6.2 Validity of Operations -- 4.6.3 The Meaning of Improper OFNs -- 4.7 Summary and Further Intuitions -- References -- 5 Processing Direction with Ordered Fuzzy Numbers -- 5.1 Introduction -- 5.2 Direction Measurement Tool -- 5.2.1 The PART Function -- 5.2.2 The Direction Determinant -- 5.3 Compatibility Between OFNs -- 5.4 Inference Sensitive to Direction -- 5.4.1 Directed Inference Operation -- 5.4.2 Examples -- 5.5 Aggregation of OFNs -- 5.5.1 The Aggregation's Basic Properties -- 5.5.2 Arithmetic Mean Directed Aggregation -- 5.5.3 Aggregation for Premise Parts of Fuzzy Rules -- 5.6 Summary -- References -- 6 Comparing Fuzzy Numbers Using Defuzzificators on OFN Shapes -- 6.1 Introduction -- 6.2 Formal Approach to the Problem -- 6.3 Defuzzification Methods -- 6.3.1 Defuzzification Methods for OFN -- 6.4 Definition of Golden Ratio Defuzzification Operator -- 6.4.1 Golden Ratio for OFN -- 6.5 Golden Ratio -- 6.6 Defuzzification Conditions for GR -- 6.6.1 Normalization -- 6.6.2 Restricted Additivity -- 6.6.3 Homogeneity -- 6.7 Definition of Mandala Factor Defuzzification Operator -- 6.8 Mandala Factor -- 6.9 Defuzzification Conditions for MF -- 6.9.1 Normalization -- 6.9.2 Restricted Additivity -- 6.9.3 Homogeneity -- 6.10 Catalogue of the Shapes of Numbers in OFN Notation -- 6.11 Conclusion -- References -- 7 Two Approaches to Fuzzy Implication -- 7.1 Introduction -- 7.2 Lattice Structure and Implications on SOFNs -- 7.2.1 Step-Ordered Fuzzy Numbers -- 7.2.2 Lattice on mathcalRK -- 7.2.3 Complements and Negation on calN -- 7.2.4 Fuzzy Implication on BSOFN -- 7.2.5 Applications -- 7.3 Metasets -- 7.3.1 The Binary Tree T and the Boolean Algebra mathfrakB -- 7.3.2 General Definition of Metaset -- 7.3.3 Interpretations of Metasets -- 7.3.4 Forcing -- 7.3.5 Set-Theoretic Relations for Metasets. 7.3.6 Applications of Metasets -- 7.3.7 Classical and Fuzzy Implication -- 7.4 Conclusions and Further Research -- References -- Part III Examples of Applications -- 8 OFN Capital Budgeting Under Uncertainty and Risk -- 8.1 Introduction -- 8.2 Ordered Fuzzy Numbers -- 8.3 Classic Capital Budgeting Methods -- 8.4 Fuzzy Approach to the Discount Methods -- 8.5 Computational Example of the Investment Project -- 8.6 Summary -- References -- 9 Input-Output Model Based on Ordered Fuzzy Numbers -- 9.1 Introduction -- 9.2 Input-Output Analysis -- 9.3 Example of Application of OFNs in the Leontief Model -- 9.4 Conclusions -- References -- 10 Ordered Fuzzy Candlesticks -- 10.1 Introduction -- 10.2 Ordered Fuzzy Candlesticks -- 10.3 Volume and Spread -- 10.3.1 Volume -- 10.3.2 Spread -- 10.4 Ordered Fuzzy Candlesticks in Technical Analysis -- 10.4.1 Ordered Fuzzy Technical Analysis Indicators -- 10.4.2 Ordered Fuzzy Candlestick as Technical Analysis Indicator -- 10.5 Ordered Fuzzy Time Series Models -- 10.6 Conclusion and Future Works -- References -- 11 Detecting Nasdaq Composite Index Trends with OFNs -- 11.1 Introduction -- 11.2 Application of OFN Notation for the Fuzzy Observation of NASDAQ Composite -- 11.3 Ordered Fuzzy Number Formulas -- 11.4 Conclusions -- References -- 12 OFNAnt Method Based on TSP Ant Colony Optimization -- 12.1 Introduction -- 12.2 Application of Ant Colony Algorithms in Searching for the Optimal Route -- 12.3 OFNAnt, a New Ant Colony Algorithm -- 12.4 Experiment -- 12.4.1 Experiment Execution Method -- 12.4.2 Software Used for Experiment -- 12.4.3 Experimental Data -- 12.5 Results of Experiment -- 12.6 Summary and Conclusions -- References -- 13 A New OFNBee Method as an Example of Fuzzy Observance Applied for ABC Optimization -- 13.1 Introduction -- 13.2 ABC (Artificial Bee Colony) Model -- 13.3 Selected OFN Issues. 13.4 New Hybrid OFNBee Method -- 13.5 Experimental Results -- 13.6 Conclusion -- References -- 14 Fuzzy Observation of DDoS Attack -- 14.1 Introduction -- 14.2 DDoS Attack Description and Recognition -- 14.3 The Idea of Attack Recognition and Prevention -- 14.4 Attack Observation Using OFNs -- 14.5 Experiment Test Results -- 14.5.1 Test Description -- 14.5.2 Attack Detection Using Proposed Method -- 14.6 Conclusions-Method Comparision -- References -- 15 Fuzzy Control for Secure TCP Transfer -- 15.1 Introduction -- 15.2 Multipath TCP -- 15.3 Multipath TCP Schedulers -- 15.3.1 Multipath TCP Standard Scheduler -- 15.3.2 Multipath TCP Secure Scheduler -- 15.3.3 Multipath TCP Scheduler with OFN Usage -- 15.3.4 OFN for Problem Detection -- 15.4 OFN Scheduler Algorithm -- 15.5 Simulation Test Results -- 15.6 Conclusions -- References -- 16 Fuzzy Numbers Applied to a Heat Furnace Control -- 16.1 Introduction -- 16.2 Selected Definitions -- 16.2.1 The Essence of Ordered Fuzzy Numbers -- 16.2.2 Fuzzy Controller -- 16.2.3 Control of the Stove on Solid Fuel -- 16.3 Classic Fuzzy Controller -- 16.4 The Controller for the OFNs -- 16.4.1 Directed OFN as a Combustion Trend -- 16.5 Modeling Trend in the Inference Process -- 16.6 Conclusions -- References -- 17 Analysis of Temporospatial Gait Parameters -- 17.1 Introduction -- 17.2 Methods -- 17.2.1 Subjects -- 17.2.2 Methods -- 17.2.3 Statistical Analysis -- 17.2.4 Fuzzy-Based Tool for Gait Assessment -- 17.2.5 Main Ideas of the OFN Model -- 17.2.6 OFN Model in Gait Assessment -- 17.3 Results -- 17.4 Discussion -- 17.5 Conclusions -- References -- 18 OFN-Based Brain Function Modeling -- 18.1 Introduction -- 18.2 State of the Art -- 18.2.1 Theory -- 18.2.2 Modeling Complex Ideas with Fuzzy Systems -- 18.2.3 Clinical Practice -- 18.2.4 Models for Linking Hypotheses and Experimental Studies -- 18.3 Concepts. 18.3.1 Data Ladder -- 18.3.2 Models of a Single Neuron -- 18.3.3 Models of Biologically Relevant Neural Networks -- 18.3.4 Models of Human Behavior -- 18.4 Traditional versus Fuzzy Approach -- 18.5 OFN as an Alternative Approach to Fuzziness -- 18.6 Patterns and Examples -- 18.6.1 Intuitive Modeling of the Complex Functions -- 18.6.2 Improving Policy Gradient Method -- 18.6.3 Modeling Learning Rate with the OFNs -- 18.7 Discussion -- 18.7.1 Results of Other Scientists -- 18.7.2 Limitations of Our Approach and Directions for Further Research -- 18.8 Conclusions -- References. |
| Record Nr. | UNINA-9910231246403321 |
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Łukasz Apiecionek
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| Springer Nature, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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