A new paradigm of knowledge engineering by soft computing /

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Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allo...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores Corporativos: Fuzzy Logic Systems Institute, International Conference on Soft Computing
Otros Autores: Ding, Liya
Formato: Electrónico Congresos, conferencias eBook
Idioma:Inglés
Publicado: Singapore ; River Edge, NJ : World Scientific, ©2001.
Colección:FLSI soft computing series ; v. 5.
Temas:
Soft computing > Congresses.
Fuzzy systems > Congresses.
Expert systems (Computer science) > Congresses.
Soft computing.
Fuzzy systems.
Expert systems (Computer science)
Expert Systems
Informatique douce.
Systèmes flous.
Systèmes experts (Informatique)
Informatique douce > Congrès.
Systèmes flous > Congrès.
Systèmes experts (Informatique) > Congrès.
COMPUTERS > Enterprise Applications > Business Intelligence Tools.
COMPUTERS > Intelligence (AI) & Semantics.
Fuzzy systems
Soft computing
Conference papers and proceedings
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Series Editor's Preface ; Volume Editor's Preface ; Chapter 1 Knowledge Engineering and Soft Computing
  • An Introduction ; Part I: Fuzzy Knowledge-Based Systems ; Chapter 2 Linguistic Integrity: A Framework for Fuzzy Modeling
  • AFRELI Algorithm ; Chapter 3 A New Approach to Acquisition of Comprehensible Fuzzy Rules
  • Chapter 4 Fuzzy Rule Generation with Fuzzy Singleton-Type Reasoning Method Chapter 5 Antecedent Validity Adaptation Principle for Table Look-Up Scheme ; Chapter 6 Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases ; Chapter 7 Revision Principle Applied for Approximate Reasoning
  • Chapter 8 Handling Null Queries with Compound Fuzzy Attributes Chapter 9 Fuzzy System Description Language ; Part II: Knowledge Representation, Integration and Discovery by Soft Computing; Chapter 10 Knowledge Representation and Similarity Measure in Learning a Vague Legal Concept
  • Chapter 11 Trend Fuzzy Sets and Recurrent Fuzzy Rules for Ordered Dataset Modelling Chapter 12 Approaches to the Design of Classification Systems from Numerical Data and Linguistic Knowledge ; Chapter 13 A Clustering based on Self-Organizing Map and Knowledge Discovery by Neural Network
  • Chapter 14 Probabilistic Rough Induction Chapter 15 Data Mining via Linguistic Summaries of Databases:An Interactive Approach ; About the Authors ; Keyword Index

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