AIMC Topic: Coal

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Stability Risk Assessment of Underground Rock Pillars Using Logistic Model Trees.

International journal of environmental research and public health Feb 14, 2022
Pillars are important structural elements that provide temporary or permanent support in underground spaces. Unstable pillars can result in rock sloughing leading to roof collapse, and they can also cause rock burst. Hence, the prediction of undergro...
Machine Learning Coal Compressive Strength Risk Assessment Logistic Models
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Coal identification based on a deep network and reflectance spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 6, 2022
The rapid identification of coal types in the field is an important task. This research combines spectroscopy with deep learning algorithms and proposes a method for quickly identifying coal types in the field. First, we collect field spectral data o...
Spectrum Analysis Algorithms Coal Neural Networks, Computer
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Early Warning of Gas Concentration in Coal Mines Production Based on Probability Density Machine.

Sensors (Basel, Switzerland) Aug 25, 2021
Gas explosion has always been an important factor restricting coal mine production safety. The application of machine learning techniques in coal mine gas concentration prediction and early warning can effectively prevent gas explosion accidents. Nea...
China Machine Learning Probability Algorithms Coal
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Diffuse reflectance spectroscopy based rapid coal rank estimation: A machine learning enabled framework.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 5, 2021
This research aims at studying the ability of using diffuse reflectance spectroscopy (DRS) for discriminating or classifying coal samples into different ranks. Spectral characteristics such as the shape of the spectral profile, slope, absorption inte...
Algorithms Support Vector Machine Machine Learning Coal Spectrum Analysis
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A Synchronous Prediction Model Based on Multi-Channel CNN with Moving Window for Coal and Electricity Consumption in Cement Calcination Process.

Sensors (Basel, Switzerland) Jun 23, 2021
The precision and reliability of the synchronous prediction of multi energy consumption indicators such as electricity and coal consumption are important for the production optimization of industrial processes (e.g., in the cement industry) due to th...
Reproducibility of Results Coal Neural Networks, Computer Forecasting Electricity
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Rule-based expert system to assess caving output ratio in top coal caving.

PloS one Sep 4, 2020
Coal mining professionals in coal mining have recognized that the assessment of top coal release rate can not only improve the recovery rate of top coal, but also improve the quality of coal. But the process was often performed using a manual-based o...
Fuzzy Logic Coal Expert Systems Mining
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Combination of minimum enclosing balls classifier with SVM in coal-rock recognition.

PloS one Sep 22, 2017
Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant a...
Statistics, Nonparametric Vibration Datasets as Topic Pattern Recognition, Automated Discriminant Analysis Coal Acoustics Support Vector Machine Nonlinear Dynamics Area Under Curve
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Co-combustion of peanut hull and coal blends: Artificial neural networks modeling, particle swarm optimization and Monte Carlo simulation.

Bioresource technology May 24, 2016
Co-combustion of coal and peanut hull (PH) were investigated using artificial neural networks (ANN), particle swarm optimization, and Monte Carlo simulation as a function of blend ratio, heating rate, and temperature. The best prediction was reached ...
Temperature Neural Networks, Computer Monte Carlo Method Coal Models, Theoretical Algorithms Uncertainty Arachis
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An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process.

Computational intelligence and neuroscience Apr 27, 2016
In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement...
Safety Disasters Public Health Humans Predictive Value of Tests Algorithms Models, Genetic Coal Computer Simulation Models, Theoretical Neural Networks, Computer Fuzzy Logic
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Application of artificial neural networks to co-combustion of hazelnut husk-lignite coal blends.

Bioresource technology Oct 8, 2015
The artificial neural network (ANN) theory is applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000°C at different heating rates in air to study co-combustion of hazelnut husk (HH)-lignite c...
Corylus Coal Neural Networks, Computer Renewable Energy Thermogravimetry Temperature
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