CONTENTS -- 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 -- Foundations of Many-Valued Reasoning D. Mundici -- References -- 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 -- Field Theory and Computing with Words G. Resconi and M Nikravesh -- 1. 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 -- 3.4. Generalized Enough Modifier -- 4. 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 -- Numerical Implementation Strategies of the Fuzzy Finite Element Method for Application in Structural Dynamics D. Moens and D. Vandepitte -- 1. 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 -- Environmental/Economic Dispatch Using Genetic Algorithm and Fuzzy Number Ranking Method G. Zhang, G. Zhang, 1. Lu, and H. Lu -- 1. Introduction -- 2. Fuzzy Dynamic Environmental Economic Load Dispatch Model -- 3. Weighting Ideal Point Method and Hybrid Genetic Algorithm -- 3.1 Weighing Ideal Point Method -- 3.2 Quasi-Simplex Techniques -- 4. Experiment Results -- 4.1. Objective Function -- 4.2 Test Data -- 4.3 Test Results -- 5. Conclusions -- References -- Minimizing the Number of Affected Concepts in Handling Inconsistent Knowledge E. Gregoire -- 1. Introduction -- 2. Semantic-oriented approaches -- 3. A refined semantic-based approach -- 4. Example -- S. Conclusions -- References -- A Knowledge Management based Fuzzy Model for Intelligent Information Disposal X Liang, Z. Zhang, D. Zhu, and B. Tang -- 1. Introduction -- 2. Human's thinking activity processes -- 2.1. Judgment thinking process.

2.2. Decision thinking process -- 3. The fuzzy model base of intelligent information disposal -- 3.1. Fuzzy logic inference Model of abstract thinking -- 3.2. Fuzzy pattern recognition model o/imagination thinking -- 3.3. Fuzzy state equation model of intuitive thinking -- 4. Conclusions -- References -- A Semantical Assistant Method for Grammar Parsing Y Wang, G. Gan, Z. Wu, and F. Li -- 1. Introduction -- 2. The ideal of semantic assistant for grammar parsing -- 3. Knowledge representation for the semantic of phrase -- 3.1. Scenarized knowledge representation (SKR) -- 4. Checking the weak-consistency of the semantic knowledge of phrase -- 5. Experiment -- 6. Conclusion -- References -- Lukasiewicz Algebra Model of Linguistic Values of Truth and Their Reasoning L. Yi, Z. Pei, and Y Xu -- 1. Introduction -- 2. Ordering structure in domain of linguistic "'!ruth" -- 3. Lukasiewicz algebra model of (T', ~f) -- 4. Lukasiewicz algebra model of extended linguistic domain -- 5. Reasoning by directly handling linguistic values of Truth -- 6. Conclusion -- Acknowledgments -- References -- Propositional Logic L6P(X) based on Six Linguistic Term Lattice Implication Algebra W. Wang, Y Xu, and L. Zou -- 1. Introduction -- 2. The properties of L6 and L6P(X) -- 3. Generalized literals of L6P(X) -- 4. Conclusions -- References -- Weighting Qualitative Fuzzy First-Order Logic and its Resolution Method L. Zou, B. Li, W. Wang, and Y. Xu -- 1. Introduction -- 2. Qualitative fuzzy logic system -- 3. A resolution method -- 4. Conclusions -- References -- Annihilator and Alpha-Subset X Q. Long, Y Xu, and L.z. Yi -- 1. Introduction -- 2. Preliminaries -- 3. Annihilators -- 4. a - subsets -- 5. Conclusion -- Acknowledgement -- References -- Multi-Fold Fuzzy Implicative Filter of Residuated Lattice Implication Algebras H. Zhu, 1. Zhao, Y. Xu, and L. Yi -- 1. Introduction.

2. Preliminaries -- 3. Multi-fold fuzzy implicative filter -- References -- PD-Algebras Y. Liu and Y. Xu -- 1. pseudoeffect algebras and pseudo-difference posets -- 2. Axiom systems of pseudo-difference posets -- 3. P D-algebras -- References -- Li-Yorke Chaos in a Spatiotemporal Chaotic System P. Li, Z.Li, WA. Haiang, and G. Chen -- 1. Introduction -- 2. Li-Yorke chaos and Marotto theorem -- 3. Li-Yorke Chaos in CML -- 4. Simulation -- 5. Conclusions -- 6. Acknowledge -- References -- On the Probability and Random Variables on IF Events B. Riecan -- 1. Introduction -- 2. Probability -- 3. Observable -- 4. Conclusion -- References -- Another Approach to Test the Reliability of a Model for Calculating Fuzzy Probabilities C. Huang and D. Jia -- 1. Introduction -- 2. Basic Terminologies -- 2.1. Uncertainty, probability and possibility -- 2.2. Fuzzy probability -- 2.3. Possibility-probability distribution -- 2.4. Histogram estimate -- 3. Interior-Outer-Set Model -- 4. Description of the New Approach -- 5. A Numerical Simulation Experiment -- Acknowledgment -- References -- A Novel Gaussian Processes Model for Regression and Prediction Y Zhou, T Zhang, and Z. Lu -- 1. Introduction -- 2. A review on GP model -- 3. Proposed MGP model -- 4. Experiments -- 4.1. One dimensional toy example -- 4.2. Two dimensional toy example -- 4.3. Real-word prediction problem -- 5. Conclusions -- References -- On PCA Error of Subject Classification L.H. Feng, F.s. Hu, and L. Wan -- 1. Introduction -- 2. peA Theory and Method -- 3. Error Discussion of PCA Classification -- 3.1. The Discrimination Ability of peA is Limited -- 3.2. For Those Samples with Big Variables, PCA Losses its Ability 0/ Discrimination -- 3.3. When the Value o/Variable Increases, on the Contrary, Class Level Decreases -- 3.4. The Same Samples, while Different Classifications.

3.5. Variables Change a Lot, while Classification Keeps Unchanged -- 3.6. While Variables Change Arbitrarily, There Are Only Two Different Classifications -- 3.7. The Position Change of Variables Causes the Change of Classification -- 3.8. The Change ofa Variable Causes the Change of the Classification -- 4. Conclusion -- References -- Optimized Algorithm of Discovering Functional Dependencies with Degrees of Satisfaction Q. Wei and G. Chen -- 1. Introduction -- 2. Preliminaries -- 3. Optimized Sub-Algorithm of Computing the Degree of Satisfaction -- 4. (FDs)d Inference Rules -- 5. Optimized MFDD Algorithm -- 6. A Small Example -- 7. Concluding Remarks -- References -- From Analogy Reasoning to Instances based Learning W Pan and T Li -- 1. Introduction -- 2. The Representation of Structures -- 3. Structures mapping in Analogy Reasoning -- 4. Classification on Real-valued Data by Local Structure Mapping -- 4.1. Selecting the Structure for Training Data -- 4.2. Determining the Local Structures for an Instance Related to Training Data -- 4.3. Approximating New Instances' Target Values Based on Their Local Structures -- 4.4. Experiment Study -- 5. Conclusion -- References -- A Kind of Weak Ratio Rules for Forecasting Upper Bound Q. Wei, B. Jiang, K. Wu, and W Wang -- 1. Introduction -- 2. Problem Statement -- 3. Mining Algorithm -- 4. Uncertainty reasoning -- 5. Application -- 6. Conclusion -- References -- Combining Validity Indexes and Multi-Objective Optimization based Clustering T dzyer and R. Alhajj -- 1. Introduction -- 2. The Clustering Process -- 2.1. Finding Alternative Solutions -- 2.2. Deciding on Number of Clusters -- 2.3. Applying CURE for Actual clustering -- 3. Experiments and Results -- 4. Conclusions -- References.

A Method for Reducing Linguistic Terms in Sensory Evaluation Using Principle of Rough Set Theory X Liu, X Zeng, L. Koehl, and Y Xu.