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    GECCO
    2006
    Springer
    159views Optimization» more  GECCO 2006»
    Identification of weak motifs in multiple biological sequences using genetic algorithm
    15 years 1 months ago
    Identification of weak motifs in multiple biological sequences using genetic algorithm
    Download  www.cs.york.ac.uk
    Recognition of motifs in multiple unaligned sequences provides an insight into protein structure and function. The task of discovering these motifs is very challenging because mos...
    Topon Kumar Paul, Hitoshi Iba
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    ICGA
    1993
    296views Optimization» more  ICGA 1993»
    A Genetic Algorithm Applied to the Maximum Flow Problem
    14 years 11 months ago
    A Genetic Algorithm Applied to the Maximum Flow Problem
    Download  cis.csuohio.edu
    A genetic algorithms is applied to find a maximum flow from the source to sink in a weighted directed graph, where the weight associated with each edge represents its flow capacit...
    Toshinori Munakata, David J. Hashier
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    IJCAI
    1989
    110views Artificial Intelligence» more  IJCAI 1989»
    Training Feedforward Neural Networks Using Genetic Algorithms
    14 years 11 months ago
    Training Feedforward Neural Networks Using Genetic Algorithms
    Download  dli.iiit.ac.in
    Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
    David J. Montana, Lawrence Davis
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    APIN
    2007
    118views more  APIN 2007»
    Using genetic algorithms to reorganize superpeer structure in peer to peer networks
    14 years 10 months ago
    Using genetic algorithms to reorganize superpeer structure in peer to peer networks
    Download  www.ai.uga.edu
    In this thesis, we describe a genetic algorithm for optimizing the superpeer structure of semantic peer to peer networks. Peer to peer, also called P2P, networks enable us to sear...
    Jaymin Kessler, Khaled Rasheed, Ismailcem Budak Ar...
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    GECCO
    2005
    Springer
    126views Optimization» more  GECCO 2005»
    Not all linear functions are equally difficult for the compact genetic algorithm
    15 years 3 months ago
    Not all linear functions are equally difficult for the compact genetic algorithm
    Download  www.cs.bham.ac.uk
    Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
    Stefan Droste
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