A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such...

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Veröffentlicht in:	Computers & geosciences Jg. 42; S. 18 - 27
Hauptverfasser:	Tahmasebi, Pejman, Hezarkhani, Ardeshir
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.05.2012 Pergamon Press
Schlagworte:	Adaptive systems algorithms Artificial neural networks case studies Coactive neuro-fuzzy inference system (CANFIS) computers Fuzzy logic Genetic algorithm Genetic algorithms Grade estimation Iran Learning theory Mathematical models mineralogy mining momentum Networks Neural networks Parallel optimization Iran Coactive neuro-fuzzy inference system (CANFIS) Genetic algorithm Parallel optimization Grade estimation Artificial neural networks
ISSN:	0098-3004, 1873-7803
Online-Zugang:	Volltext
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