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Full-Text Articles in Physical Sciences and Mathematics
Application Of Entropy Method For Estimating Factor Weights In Mining-Method Selection For Development Of Novel Mining-Method Selection System, Elsa Pansilvania Andre Manjate, Mahdi Saadat, Hisatoshi Toriya, Fumiaki Inagaki, Youhei Kawamura
Application Of Entropy Method For Estimating Factor Weights In Mining-Method Selection For Development Of Novel Mining-Method Selection System, Elsa Pansilvania Andre Manjate, Mahdi Saadat, Hisatoshi Toriya, Fumiaki Inagaki, Youhei Kawamura
Journal of Sustainable Mining
Mining-method selection (MMS) is one of the most critical and complex decisionmaking processes in mine planning. Therefore, it has been a subject of several studies for many years culminating with the development of different systems. However, there is still more to be done to improve and/or create more efficient systems and deal with the complexity caused by many influencing factors. This study introduces the application of the entropy method for feature selection, i.e., select the most critical factors in MMS. The entropy method is applied to assess the relative importance of the factors influencing MMS by estimating their objective weights …
Coal Mine Water Inrush Prediction Based On Lstm Neural Network, Dong Lili, Fei Cheng, Zhang Xiang, Cao Chaofan
Coal Mine Water Inrush Prediction Based On Lstm Neural Network, Dong Lili, Fei Cheng, Zhang Xiang, Cao Chaofan
Coal Geology & Exploration
According to the prediction of water inrush from coal seam floor, based on the summarization of existing water inrush prediction methods and theories, the feature selection experiment shows that water pressure, distance from the working surface, sandstone section thickness, coal thickness, coal seam inclination, fault throw, fissure zone, mining area, mining height and strike length are the main factors affecting the occurrence of water inrush. These factors are complex and non-linear. A water inrush prediction model based on long short-term memory(LSTM) neural network was proposed. The data of the coal mine water inrush case was used as sample data to …
Classification Of The Waxy Condition Of Durum Wheat By Near Infrared Reflectance Spectroscopy Using Wavelets And A Genetic Algorithm, Barry K. Lavine, Nikhil Mirjankar, Stephen Delwiche
Classification Of The Waxy Condition Of Durum Wheat By Near Infrared Reflectance Spectroscopy Using Wavelets And A Genetic Algorithm, Barry K. Lavine, Nikhil Mirjankar, Stephen Delwiche
United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications
Near infrared (NIR) reflectance spectroscopy has been applied to the problem of differentiating four genotypes of durum wheat: ‘waxy’, Wx A1 null null, wx-B1 null and wild type. The test data consisted of 95 NIR reflectance spectra of wheat samples obtained from a USDA-ARSwheat breeding program. A two-step procedure for pattern recognition analysis of NIR spectral data wasemployed. First, thewavelet packet transform [14,15] was applied to the NIR reflectance data usingwavelet filters at different scales to extract and separate low-frequency signal components from high frequency noise components. By applying these filters, each reflectance spectrum was decomposed into wavelet coefficients that …
Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.)
Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.)
OES Faculty Publications
We present a two-step algorithm for the detection of seafloor propeller seagrass scars in shallow water using panchromatic images. The first step is to classify image pixels into scar and non-scar categories based on a sparse coding algorithm. The first step produces an initial scar map in which false positive scar pixels may be present. In the second step, local orientation of each detected scar pixel is computed using the morphological directional profile, which is defined as outputs of a directional filter with a varying orientation parameter. The profile is then utilized to eliminate false positives and generate the final …