Add to ORKGAbstract: In this paper a comparison between two single classifier methods (support vector machine, artificial neural network) and two ensemble methods (bagging, and boosting) is applied to a real-world mining problem. The four methods are used to classify, thus monitoring underground dam levels and underground pumps energy consumption on a doublepump station deep gold in South Africa. In terms of misclassification error, the results show support vector machines (SVM) to be more efficient for classification of underground pumps energy consumption compared to artificial neural network (ANN),..
Introduction Mineral exploration is a process by which it is decided whether or not continuing expl...
This research aims to enhance the classification of the rock mass in underground mining, a common pr...
Unconventional reservoirs are the productive zones in other words the rock quality and the mechanica...
Abstract: In this paper a comparison between two single classifier methods (support vector machine, ...
Abstract: In this paper six single classifiers (support vector machine, artificial neural network, n...
Abstract: In this paper six single classifiers (support vector machine, artificial neural network, n...
D.Ing. (Electrical and Electronic Engineering)The electricity shortage in South Africa has required ...
D.Ing. (Electrical and Electronic Engineering)The electricity shortage in South Africa has required ...
Abstract: Four machine learning algorithms (artificial neural networks, a naive Bayes' classifier, a...
Abstract: Four machine learning algorithms (artificial neural networks, a naive Bayes' classifier, a...
Mining industry consumes a significant amount of energy and makes greenhouse gas emissions in variou...
The mining industry’s increased energy consumption has resulted in a slew of climate-related effects...
This chapter demonstrates the practical application of artificial intelligence (AI) to improve energ...
Energy saving has become an important aspect of every business activity as it is important in terms ...
The deep-level mining industry is experiencing narrowing profit margins due to increasing operating ...
Introduction Mineral exploration is a process by which it is decided whether or not continuing expl...
This research aims to enhance the classification of the rock mass in underground mining, a common pr...
Unconventional reservoirs are the productive zones in other words the rock quality and the mechanica...
Abstract: In this paper a comparison between two single classifier methods (support vector machine, ...
Abstract: In this paper six single classifiers (support vector machine, artificial neural network, n...
Abstract: In this paper six single classifiers (support vector machine, artificial neural network, n...
D.Ing. (Electrical and Electronic Engineering)The electricity shortage in South Africa has required ...
D.Ing. (Electrical and Electronic Engineering)The electricity shortage in South Africa has required ...
Abstract: Four machine learning algorithms (artificial neural networks, a naive Bayes' classifier, a...
Abstract: Four machine learning algorithms (artificial neural networks, a naive Bayes' classifier, a...
Mining industry consumes a significant amount of energy and makes greenhouse gas emissions in variou...
The mining industry’s increased energy consumption has resulted in a slew of climate-related effects...
This chapter demonstrates the practical application of artificial intelligence (AI) to improve energ...
Energy saving has become an important aspect of every business activity as it is important in terms ...
The deep-level mining industry is experiencing narrowing profit margins due to increasing operating ...
Introduction Mineral exploration is a process by which it is decided whether or not continuing expl...
This research aims to enhance the classification of the rock mass in underground mining, a common pr...
Unconventional reservoirs are the productive zones in other words the rock quality and the mechanica...