Hybrid CNN-LSTM and IoT-based coal mine hazards monitoring and prediction system
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Hybrid CNN-LSTM and IoT-based coal mine hazards monitoring and prediction system
Authors
Keywords
IoT, Deep learning, Underground coal mine, Prediction of hazards, Miner’s health quality index
Journal
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
Volume 152, Issue -, Pages 249-263
Publisher
Elsevier BV
Online
2021-06-05
DOI
10.1016/j.psep.2021.06.005
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Application of Artificial Neural Networks in Assessing Mining Subsidence Risk
- (2020) Yangkyun Kim et al. Applied Sciences-Basel
- The potential of new ensemble machine learning models for effluent quality parameters prediction and related uncertainty
- (2020) Ahmad Sharafati et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- UMAP and LSTM based fire status and explosibility prediction for sealed-off area in underground coal mine
- (2020) K. Kumari et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Review and analysis of supervised machine learning algorithms for hazardous events in drilling operations
- (2020) Augustine Uhunoma Osarogiagbon et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Forecast of daily PM2.5 concentrations applying artificial neural networks and Holt–Winters models
- (2019) Luciana Maria Baptista Ventura et al. Air Quality Atmosphere and Health
- Overcoming mine safety crisis in Pakistan: An appraisal
- (2019) Izhar Mithal Jiskani et al. PROCESS SAFETY PROGRESS
- CNNpred: CNN-based stock market prediction using a diverse set of variables
- (2019) Ehsan Hoseinzade et al. EXPERT SYSTEMS WITH APPLICATIONS
- Predicting Methane Concentration in Longwall Regions Using Artificial Neural Networks
- (2019) Tutak et al. International Journal of Environmental Research and Public Health
- Application of artificial neural networks for predicting tree survival and mortality in the Hyrcanian forest of Iran
- (2019) Mahmoud Bayat et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Application of artificial neutral network and geographic information system to evaluate retrofit potential in public school buildings
- (2019) F. Re Cecconi et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Quality control of online monitoring data of air pollutants using artificial neural networks
- (2019) Ziyu Wang et al. Air Quality Atmosphere and Health
- Ensemble method based on Artificial Neural Networks to estimate air pollution health risks
- (2019) Lilian N. Araujo et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Application of artificial intelligence to wastewater treatment: A bibliometric analysis and systematic review of technology, economy, management, and wastewater reuse
- (2019) Lin Zhao et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Review of Wearable Device Technology and Its Applications to the Mining Industry
- (2018) et al. Energies
- Hourly day-ahead solar irradiance prediction using weather forecasts by LSTM
- (2018) Xiangyun Qing et al. ENERGY
- Predicting PM 10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN)
- (2018) Sechan Park et al. JOURNAL OF HAZARDOUS MATERIALS
- Application of wireless sensor network for environmental monitoring in underground coal mines: A systematic review
- (2018) Lalatendu Muduli et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning
- (2018) et al. SENSORS
- A dynamic information platform for underground coal mine safety based on internet of things
- (2018) Yaqin Wu et al. SAFETY SCIENCE
- WLAN based energy efficient smart city design
- (2017) Sourav Hati et al. MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS
- Human health and safety risks management in underground coal mines using fuzzy TOPSIS
- (2014) Satar Mahdevari et al. SCIENCE OF THE TOTAL ENVIRONMENT
- An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring
- (2014) Yu Zhang et al. SENSORS
- Spatio-temporal characteristics of PM10 concentration across Malaysia
- (2009) Liew Juneng et al. ATMOSPHERIC ENVIRONMENT
- Forecasting gob gas venthole production performances using intelligent computing methods for optimum methane control in longwall coal mines
- (2009) C. Özgen Karacan INTERNATIONAL JOURNAL OF COAL GEOLOGY
- Modeling and prediction of ventilation methane emissions of U.S. longwall mines using supervised artificial neural networks
- (2007) C. Özgen Karacan INTERNATIONAL JOURNAL OF COAL GEOLOGY
- An overview of the PM10 pollution problem, in the Metropolitan Area of Athens, Greece. Assessment of controlling factors and potential impact of long range transport
- (2007) G. Grivas et al. SCIENCE OF THE TOTAL ENVIRONMENT
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started