Forecasting gob gas venthole production performances using intelligent computing methods for optimum methane control in longwall coal mines

International Journal of Coal Geology

Volumn 79, Issue 4, 2009, Pages 131-144

  Karacan, C Özgen ^a  

^a NATIONAL INSTITUTE FOR OCCUPATIONAL SAFETY AND HEALTH   (United States)

Author keywords

Artificial neural networks; Gob gas ventholes; Longwall mining; Methane control; Production performance; Sensitivity analysis

Indexed keywords

APPALACHIAN BASIN; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; COALBEDS; DRILLING PARAMETERS; EXHAUSTERS; GAS FLOWRATE; GOB GAS VENTHOLES; HIDDEN LAYERS; INPUT VARIABLES; LONGWALL FACES; LONGWALL OPERATIONS; LONGWALLS; METHANE CONTENT; METHANE EMISSIONS; PENNSYLVANIA; PERCEPTRON; PITTSBURGH; PRACTICAL MODEL; PRODUCTION DATA; PRODUCTION PERFORMANCE; START-UPS; SURFACE ELEVATIONS; WORK ENVIRONMENTS;

BACKPROPAGATION; COAL DEPOSITS; COAL MINES; EMPLOYMENT; GASES; HUMAN ENGINEERING; INTELLIGENT COMPUTING; LONGWALL MINING; METHANATION; METHANE; MINING; NEURAL NETWORKS;

SENSITIVITY ANALYSIS;

ARTIFICIAL NEURAL NETWORK; COAL MINE; COALBED METHANE; FORECASTING METHOD; LONGWALL MINING; SENSITIVITY ANALYSIS;

APPALACHIAN BASIN; NORTH AMERICA; PENNSYLVANIA; UNITED STATES;

EID: 68549125036     PISSN: 01665162     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.coal.2009.07.005     Document Type: Article

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