Pages that link to "Item:Q3616578"
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The following pages link to MODELING THE SPATIAL DISTRIBUTION OF MINERAL DEPOSITS USING NEURAL NETWORKS (Q3616578):
Displaying 9 items.
- A mathematical view of weights-of-evidence, conditional independence, and logistic regression in terms of Markov random fields (Q887579) (← links)
- A hybrid neuro-fuzzy model for mineral potential mapping (Q943011) (← links)
- Ore grade prediction using a genetic algorithm and clustering based ensemble neural network model (Q964855) (← links)
- Comparison of machine learning methods for copper ore grade estimation (Q1715372) (← links)
- Multiple artificial neural networks with interaction noise for estimation of spatial categorical variables (Q1736824) (← links)
- Potential modeling: conditional independence matters (Q2254029) (← links)
- ARTIFICIAL NEURAL NETWORK MODELING FOR REFORESTATION DESIGN THROUGH THE DOMINANT TREES BOLE‐VOLUME ESTIMATION (Q3653134) (← links)
- AI 2003: Advances in Artificial Intelligence (Q5191613) (← links)
- Graph deep learning model for mapping mineral prospectivity (Q6062085) (← links)
