Improving the generalization performance multi-layer-perceptrons with population-based incremental learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1141, Issue , 1996, Pages 740-750

  Galić, Elvis ^a   Höhfeld, Markus ^b  

^a Department of Theoretical Physics ^*  (Germany)

^b SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EVOLUTIONARY ALGORITHMS; KNOWLEDGE ENGINEERING; NETWORK ARCHITECTURE; NEURAL NETWORKS; NEWTON-RAPHSON METHOD; NEXT GENERATION NETWORKS; OPTIMIZATION;

CONTINUOUS PARAMETERS; CORRESPONDING WEIGHTS; GENERALIZATION ABILITY; GENERALIZATION PERFORMANCE; MULTI-LAYER PERCEPTRONS; NEURAL NETWORK TRAINING; POPULATION BASED INCREMENTAL LEARNING; QUASI-NEWTON METHODS;

PROBLEM SOLVING;

EID: 84958984705     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-61723-X_1037     Document Type: Conference Paper

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