Comparison of Mathematical Methods of Potential Modeling

Mathematical Geosciences

Volumn 44, Issue 1, 2012, Pages 101-129

  Schaeben, Helmut ^a  

^a TU BERGAKADEMIE FREIBERG   (Germany)

Author keywords

method; method; Artificial neural nets; Bayes' theorem; Conditional independence; Formula of total probability; Independence of events; Independence of random variables; Logistic function; Logistic regression; Logistic regression with binary (dichotomous) predictor variables; Logits; Odds; Probability; Regression; Regression with artificial neural nets; Weights of evidence

Indexed keywords

ARTIFICIAL NEURAL NET; ARTIFICIAL NEURAL NETS; BAYES' THEOREM; CONDITIONAL INDEPENDENCES; FORMULA OF TOTAL PROBABILITY; INDEPENDENCE OF EVENTS; LOGISTIC FUNCTION; LOGISTIC REGRESSION; LOGISTIC REGRESSION WITH BINARY (DICHOTOMOUS) PREDICTOR VARIABLES; LOGITS; ODDS; REGRESSION; WEIGHTS OF EVIDENCE;

BAYESIAN NETWORKS; GENETIC PROGRAMMING; MAXIMUM LIKELIHOOD; MINERAL RESOURCES; NEURAL NETWORKS; PROBABILITY; RANDOM VARIABLES; RISK ASSESSMENT; RISK PERCEPTION; SILICATE MINERALS;

REGRESSION ANALYSIS;

ARTIFICIAL NEURAL NETWORK; BAYESIAN ANALYSIS; FUZZY MATHEMATICS; MAPPING; MAXIMUM LIKELIHOOD ANALYSIS; MINERAL DEPOSIT; MINERAL EXPLORATION; MINERALIZATION; NUMERICAL METHOD; NUMERICAL MODEL; PROBABILITY; REGRESSION ANALYSIS;

EID: 84855685088     PISSN: 18748961     EISSN: 18748953     Source Type: Journal    
DOI: 10.1007/s11004-011-9373-2     Document Type: Article

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