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200 10$aApplied artificial intelligence$b[electronic resource] $eproceedings of the 7th International FLINS Conference, Genova, Italy, 29-31 August 2006 /$fedited by Da Ruan ... [et al.]
210 $aSingapore ;$aRiver Edge, NJ $cWorld Scientific$dc2006
215 $a1 online resource (1020 p.)
300 $aDescription based upon print version of record.
311 $a981-256-690-2
320 $aIncludes bibliographical references and index.
327 $aCONTENTS; Knowledge Discovery for Customer Classification on the Principle of Maximum Profit C. Zeng, YXu, and W Xie; Foreword D. Ruan; Invited Lectures; Computation with Information Described in Natural LanguageThe Concept of Generalized-Constraint-based Computation L.A. Zadeh; Learning Techniques in Service Robotic Environment z.z. Bien, H.E. Lee, S. W Lee, and K.H. Park; 1. Introduction; 2. Human-Robot Interaction in Service Robotic Environment; 3. Learning Techniques for Service Robotic Environment; 4. Case Studies; 5. Concluding Remarks; Acknowledgment; References
327 $aFoundations of Many-Valued Reasoning D. MundiciReferences; Integrated Operations in Arctic Environments F. 0wre; Can the Semantic Web be Designed without Using Fuzzy Logic? E. Sanchez; References; The Role of Soft Computing in Applied Sciences P.P. Wang; PART 1: FOUNDATIONS AND RECENT DEVELOPMENTS; A Functional Tool for Fuzzy First Order Logic Evaluation V. Lopez, J.M Cleva, and J. Montero; 1. Introduction; 2. Software specification; 3. Evaluating Fuzzy FOL formulae; 4. Example; 5. Conclusions and future work; Acknowledgments; References
327 $aField Theory and Computing with Words G. Resconi and M Nikravesh1. Introduction; 2. Representation of the space of the fields inside a reference space; 2.1 Example of the basic field and sources; 2.2 Computation of the sources; 3. Field theory, concepts and Web search; Reference; New Operators for Context Adaptation of Mamdani Fuzzy Systems A. Botta, B. Lazzerini, and F. Marcelloni; 1. Introduction; 2. Non-Linear Scaling Function for Fuzzy Domains; 3. Fuzzy Modifiers; 3.1. Coverage-Level Modifier; 3.2. Core-Position Modifier; 3.3. Generalized Positively Modifier
327 $a3.4. Generalized Enough Modifier4. The Genetic Algorithm; 5. Example: Structure of Wages; 6. Conclusion; References; Using Parametric Functions to Solve Systems of Linear Fuzzy Equations - An Improved Algorithm A. Vroman, G. Deschrijver, and E.E. Kerre; 1. Introduction; 2. Preliminaries; 3. Solving systems of linear fuzzy equations; 3.1. Systems with one fuzzy coefficient; 3.2. Systems with two fuzzy coefficients; 3.3. Systems with more than two fuzzy coefficients; 4. Conclusion; Acknowledgment; References
327 $aNumerical Implementation Strategies of the Fuzzy Finite Element Method for Application in Structural Dynamics D. Moens and D. Vandepitte1. Introduction; 2. The Fuzzy Finite Element Method; 3. General implementation schemes for IFE analysis; 3.1. The interval arithmetic approach; 3.2. The global optimisation approach; 3.3. The vertex analysis; 4. IFE implementation strategies for structural dynamic analysis; 4.1. Eigenvalue analysis; 4.2. Frequency response analysis; 5. Conclusion; References
327 $aEnvironmental/Economic Dispatch Using Genetic Algorithm and Fuzzy Number Ranking Method G. Zhang, G. Zhang, 1. Lu, and H. Lu
330 $aFLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Applied Artificial Intelligence for Applied Research. The contributions to the seventh in the series of FLINS conferences contained in this volume cover state-of-the-art research and development in applied artificial intelligence for applied research in general and for power/nuclear engineering in particular.
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