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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Vydané v:	Computers & geosciences Ročník 42; s. 18 - 27
Hlavní autori:	Tahmasebi, Pejman, Hezarkhani, Ardeshir
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Ltd 01.05.2012 Pergamon Press
Predmet:	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
On-line prístup:	Získať plný text
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