Add to ORKGComparing performance of interval neutrosophic sets and neural networks with support vector machines for binary classification problem
In the modern era of diminishing returns on fixed exploration budgets, challenging targets, and ever...
The mining industry relies heavily upon empirical analysis for design and prediction. Neural networ...
The automatic classification of large numbers of mineral samples is a practical problem in mining re...
In the mining industry, effective use of geographic information systems (GIS) to identify new geogra...
Qnantification of unsertilnty in mineral prospectivity prediction is an important process tn support...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
The object of research is the processes of beneficiation of iron ore in the conditions of a mining a...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
A multilayer feed‐forward neural network, trained with a gradient descent, back‐propagation algorith...
This paper explores the novel technique of artificial neural networks and their application to miner...
Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), regression trees (RTs)...
The object of research is the processes of beneficiation of iron ore in the conditions of a mining a...
This paper presents an approach to the prediction of mineral prospectivity that provides an assessme...
Abstract. This paper explores the novel technique of artificial neural networks and their applicatio...
Geo-statistical methods for reserve estimation are difficult to use when stationary conditions are n...
In the modern era of diminishing returns on fixed exploration budgets, challenging targets, and ever...
The mining industry relies heavily upon empirical analysis for design and prediction. Neural networ...
The automatic classification of large numbers of mineral samples is a practical problem in mining re...
In the mining industry, effective use of geographic information systems (GIS) to identify new geogra...
Qnantification of unsertilnty in mineral prospectivity prediction is an important process tn support...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
The object of research is the processes of beneficiation of iron ore in the conditions of a mining a...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
A multilayer feed‐forward neural network, trained with a gradient descent, back‐propagation algorith...
This paper explores the novel technique of artificial neural networks and their application to miner...
Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), regression trees (RTs)...
The object of research is the processes of beneficiation of iron ore in the conditions of a mining a...
This paper presents an approach to the prediction of mineral prospectivity that provides an assessme...
Abstract. This paper explores the novel technique of artificial neural networks and their applicatio...
Geo-statistical methods for reserve estimation are difficult to use when stationary conditions are n...
In the modern era of diminishing returns on fixed exploration budgets, challenging targets, and ever...
The mining industry relies heavily upon empirical analysis for design and prediction. Neural networ...
The automatic classification of large numbers of mineral samples is a practical problem in mining re...