Analysis and comparison of aircraft landing control using recurrent neural networks and genetic algorithms approaches

Neurocomputing

Volumn 71, Issue 16-18, 2008, Pages 3224-3238

  Juang, Jih Gau ^a   Chiou, Hou Kai ^b   Chien, Li Hsiang ^a  

^a NATIONAL TAIWAN OCEAN UNIVERSITY   (Taiwan)

^b ASUSTEK COMPUTER INC   (Taiwan)

Author keywords

Automatic landing system; Genetic algorithms; Recurrent neural networks; Wind disturbance

Indexed keywords

AIRCRAFT; AIRCRAFT LANDING; AIRCRAFT LANDING SYSTEMS; ALGORITHMS; CONTROL SYSTEM ANALYSIS; CONTROL THEORY; CONVERGENCE OF NUMERICAL METHODS; GENETIC ALGORITHMS; GENETIC ENGINEERING; LANDING; NEURAL NETWORKS; PARAMETER ESTIMATION; REINFORCEMENT LEARNING;

AIRCRAFT LANDING CONTROLS; AND GENETIC ALGORITHMS; AUTOMATIC LANDING CONTROLLERS; AUTOMATIC LANDING SYSTEM; AUTOMATIC LANDING SYSTEMS; CONTROL SCHEMES; CONVERGENCE ANALYSIS; CROSSOVER METHODS; ERROR FUNCTIONS; INTELLIGENT CONTROLLERS; OPTIMAL CONTROLS; SAFE LANDINGS; SYSTEM ERRORS; WIND DISTURBANCE;

RECURRENT NEURAL NETWORKS;

AIRCRAFT; ALTITUDE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; COMPUTER SIMULATION; COMPUTER SYSTEM; CONFERENCE PAPER; CONTROL SYSTEM; CONTROLLED STUDY; GENETIC ALGORITHM; INTERMETHOD COMPARISON; PRIORITY JOURNAL; PROCESS OPTIMIZATION; WIND;

EID: 56549118766     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.04.044     Document Type: Conference Paper

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