Engineering Evolutionary Intelligent Systems

Evolutionary design of intelligent systems is gaining much popularity due to its capabilities in handling several real world problems involving optimization, complexity, noisy and non-stationary environment, imprecision, uncertainty and vagueness. This edited volume 'Engineering Evolutionary In...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Abraham, Ajith (Επιμελητής έκδοσης), Grosan, Crina (Επιμελητής έκδοσης), Pedrycz, Witold (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
Σειρά:Studies in Computational Intelligence, 82
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews
  • Genetically Optimized Hybrid Fuzzy Neural Networks: Analysis and Design of Rule-based Multi-layer Perceptron Architectures
  • Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design
  • Evolution of Inductive Self-organizing Networks
  • Recursive Pattern based Hybrid Supervised Training
  • Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC)
  • Evolutionary Approaches to Rule Extraction from Neural Networks
  • Cluster-wise Design of Takagi and Sugeno Approach of Fuzzy Logic Controller
  • Evolutionary Fuzzy Modelling for Drug Resistant HIV-1 Treatment Optimization
  • A New Genetic Approach for Neural Network Design
  • A Grammatical Genetic Programming Representation for Radial Basis Function Networks
  • A Neural-Genetic Technique for Coastal Engineering: Determining Wave-induced Seabed Liquefaction Depth
  • On the Design of Large-scale Cellular Mobile Networks Using Multi-population Memetic Algorithms
  • A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem
  • Particle Swarm Optimization with Mutation for High Dimensional Problems.