Hybrid intelligent methodology to design translation invariant morphological operators for Brazilian stock market prediction

Neural Networks

Volumn 23, Issue 10, 2010, Pages 1238-1251

  Araújo, Ricardo de A ^a  

^a Information Technology Department   (Brazil)

Author keywords

Financial time series prediction; Hybrid intelligent systems; Mathematical morphology; Morphological neural networks; Quantum inspired evolutionary algorithms; Stock market prediction; Translation invariant morphological operators

Indexed keywords

FINANCIAL TIME SERIES PREDICTIONS; HYBRID INTELLIGENT SYSTEM; MORPHOLOGICAL NEURAL NETWORKS; QUANTUM INSPIRED EVOLUTIONARY ALGORITHM; STOCK MARKET PREDICTION; TRANSLATION INVARIANTS;

BACKPROPAGATION; COMMERCE; EVOLUTIONARY ALGORITHMS; FINANCE; FINANCIAL DATA PROCESSING; FORECASTING; INTELLIGENT SYSTEMS; MATHEMATICAL MODELS; MATHEMATICAL MORPHOLOGY; MORPHOLOGY; NEURAL NETWORKS; PARAMETER ESTIMATION; PHASE SPACE METHODS; RANDOM PROCESSES; STATISTICAL TESTS; TIME SERIES; TIME SERIES ANALYSIS;

MATHEMATICAL OPERATORS;

ARTICLE; BRAZIL; CONTROLLED STUDY; EVOLUTIONARY ALGORITHM; INTELLIGENCE; MARKET; MATHEMATICAL ANALYSIS; METHODOLOGY; NERVE CELL NETWORK; PERFORMANCE; PREDICTION; PRIORITY JOURNAL; QUANTUM THEORY; RANDOMIZATION; STOCK MARKET; TIME SERIES ANALYSIS;

ALGORITHMS; BRAZIL; COMPUTER SIMULATION; FORECASTING; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER);

EID: 78149499489     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2010.06.007     Document Type: Article

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