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Full-Text Articles in Mining Engineering
Evaluating The Performance Of Extreme Learning Machine Technique For Ore Grade Estimation, Clara Akalanya Abuntori, Sulemana Al-Hassan, Daniel Mireku-Gyimah, Yao Yevenyo Ziggah
Evaluating The Performance Of Extreme Learning Machine Technique For Ore Grade Estimation, Clara Akalanya Abuntori, Sulemana Al-Hassan, Daniel Mireku-Gyimah, Yao Yevenyo Ziggah
Journal of Sustainable Mining
Due to the complex geology of vein deposits and their erratic grade distributions, there is the tendency of overestimating or underestimating the ore grade. These estimated grade results determine the profitability of mining the ore deposit or otherwise. In this study, five Extreme Learning Machine (ELM) variants based on hard limit, sigmoid, triangular basis, sine and radial basis activation functions were applied to predict ore grade. The motive is that the activation function has been identified to play a key role in achieving optimum ELM performance. Therefore, assessing the extent of influence the activation functions will have on the final …
Design And Development Of A Machine Vision System Using Artificial Neural Network-Based Algorithm For Automated Coal Characterization, Amit Kumar Gorai, Simit Raval, Ashok Kumar Patel, Snehamoy Chatterjee, Tarini Gautam
Design And Development Of A Machine Vision System Using Artificial Neural Network-Based Algorithm For Automated Coal Characterization, Amit Kumar Gorai, Simit Raval, Ashok Kumar Patel, Snehamoy Chatterjee, Tarini Gautam
Michigan Tech Publications
Coal is heterogeneous in nature, and thus the characterization of coal is essential before its use for a specific purpose. Thus, the current study aims to develop a machine vision system for automated coal characterizations. The model was calibrated using 80 image samples that are captured for different coal samples in different angles. All the images were captured in RGB color space and converted into five other color spaces (HSI, CMYK, Lab, xyz, Gray) for feature extraction. The intensity component image of HSI color space was further transformed into four frequency components (discrete cosine transform, discrete wavelet transform, discrete Fourier …