Using ant colony optimization-based selected features for predicting post-synaptic activity in proteins

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

Volumn 4973 LNCS, Issue , 2008, Pages 12-23

  Basiri, Mohammad Ehsan ^a   Ghasem Aghaee, Nasser ^a   Aghdam, Mehdi Hosseinzadeh ^a  

^a UNIVERSITY OF ISFAHAN   (Iran)

Author keywords

Ant Colony Optimization (ACO); Bioinformatics; Feature selection; Particle Swarm Optimization (PSO)

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; BIOCOMMUNICATIONS; BIOINFORMATICS; BOOLEAN FUNCTIONS; CLASSIFICATION (OF INFORMATION); COMPUTATIONAL COMPLEXITY; CONSTRAINED OPTIMIZATION; DATA MINING; DECISION SUPPORT SYSTEMS; EVOLUTIONARY ALGORITHMS; FEATURE EXTRACTION; INFORMATION MANAGEMENT; INFORMATION SCIENCE; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS; MINING; OPTIMIZATION; POPULATION STATISTICS; ROBOT LEARNING; SEARCH ENGINES; STANDARDS;

ANT COLONY OPTIMIZATION (ACO); BINARY PSO ALGORITHM; CLASSIFICATION SYSTEMS; DATA SETS; EUROPEAN; EVOLUTIONARY COMPUTATION (EC); FEATURE EXTRACTION (FE); FEATURE SELECTION (FS); FEATURE SELECTION METHODS; HEIDELBERG (CO); MACHINE-LEARNING; OPTIMIZATION ALGORITHMS; PARTICLE SWARM OPTIMIZATION (PSO); SIMULATION RESULTS; SYNAPTIC ACTIVITY;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 47249156145     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-78757-0_2     Document Type: Conference Paper

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