Recent advances in applications of artificial intelligence in solid waste management: A review
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Recent advances in applications of artificial intelligence in solid waste management: A review
Authors
Keywords
-
Journal
CHEMOSPHERE
Volume 309, Issue -, Pages 136631
Publisher
Elsevier BV
Online
2022-09-29
DOI
10.1016/j.chemosphere.2022.136631
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An implementation framework of blockchain-based hazardous waste transfer management system
- (2022) Guanghan Song et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Biohydrogen production from real industrial wastewater: Potential bioreactors, challenges in commercialization and future directions
- (2022) Muhammad Abdul Qyyum et al. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
- A machine learning approach for investigating the impact of seasonal variation on physical composition of municipal solid waste
- (2022) Oluwatobi Adeleke et al. Journal of Reliable Intelligent Environments
- Harvesting biohydrogen from industrial wastewater: Production potential, pilot-scale bioreactors, commercialization status, techno-economics, and policy analysis
- (2022) Muhammad Abdul Qyyum et al. Journal of Cleaner Production
- Computer vision for solid waste sorting: A critical review of academic research
- (2022) Weisheng Lu et al. WASTE MANAGEMENT
- The role of performance metrics in comparative LCA of concrete mixtures incorporating solid wastes: A critical review and guideline proposal
- (2022) Alireza Haji Hossein et al. WASTE MANAGEMENT
- Prediction of electric vehicle charging duration time using ensemble machine learning algorithm and Shapley additive explanations
- (2022) Irfan Ullah et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Municipal solid waste generation and the current state of waste-to-energy potential: State of art review
- (2022) Afzal Husain Khan et al. ENERGY CONVERSION AND MANAGEMENT
- Modeling retroreflectivity degradation of traffic signs using artificial neural networks
- (2022) Arshad Jamal et al. IATSS Research
- Waste to wealth: A critical analysis of resource recovery from desalination brine
- (2022) Ihsanullah Ihsanullah et al. DESALINATION
- An evolutionary machine learning approach for municipal solid waste generation estimation utilizing socioeconomic components
- (2021) Forough Ghanbari et al. Arabian Journal of Geosciences
- Variables Influencing per Capita Production, Separate Collection, and Costs of Municipal Solid Waste in the Apulia Region (Italy): An Experience of Deep Learning
- (2021) Fabrizio Fasano et al. International Journal of Environmental Research and Public Health
- A hybrid model for carbon price forecasting using GARCH and long short-term memory network
- (2021) Yumeng Huang et al. APPLIED ENERGY
- Intelligent solid waste classification using deep convolutional neural networks
- (2021) A. Altikat et al. International Journal of Environmental Science and Technology
- Electric vehicle energy consumption prediction using stacked generalization: an ensemble learning approach
- (2021) Irfan Ullah et al. International Journal of Green Energy
- Applications of artificial intelligence in water treatment for the optimization and automation of the adsorption process: Recent advances and prospects
- (2021) Gulzar Alam et al. CHEMICAL ENGINEERING JOURNAL
- Utilization of process network synthesis and machine learning as decision-making tools for municipal solid waste management
- (2021) R. A. Ali et al. International Journal of Environmental Science and Technology
- Developing a wavelet-AI hybrid model for short- and long-term predictions of the pollutant concentration of particulate matter10
- (2021) S. M. Mirzadeh et al. International Journal of Environmental Science and Technology
- Development of machine learning - based models to forecast solid waste generation in residential areas: A case study from Vietnam
- (2021) X. Cuong Nguyen et al. RESOURCES CONSERVATION AND RECYCLING
- Comparative performance analysis of support vector regression and artificial neural network for prediction of municipal solid waste generation
- (2021) Majeed S Jassim et al. WASTE MANAGEMENT & RESEARCH
- Predicting municipal solid waste using a coupled artificial neural network with archimedes optimisation algorithm and socioeconomic components
- (2021) Guoxi Liang et al. Journal of Cleaner Production
- Prediction of gas yield generated by energy recovery from municipal solid waste using deep neural network and moth-flame optimization algorithm
- (2021) Libing Yang et al. Journal of Cleaner Production
- Prediction of the shear modulus of municipal solid waste (MSW): An application of machine learning techniques
- (2021) Pourya Alidoust et al. Journal of Cleaner Production
- Injury severity prediction of traffic crashes with ensemble machine learning techniques: a comparative study
- (2021) Arshad Jamal et al. International Journal of Injury Control and Safety Promotion
- Technologies for municipal solid waste management: Current status, challenges, and future perspectives
- (2021) Shamshad Khan et al. CHEMOSPHERE
- Estimation of municipal solid waste amount based on one-dimension convolutional neural network and long short-term memory with attention mechanism model: A case study of Shanghai
- (2021) Kunsen Lin et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Comparing AI-Based and Traditional Prospect Generating Methods
- (2021) Christian Stadlmann et al. Journal of Promotion Management
- Current solid waste management strategies and energy recovery in developing countries - State of art review
- (2021) Afzal Husain Khan et al. CHEMOSPHERE
- Waste Management System Using IoT-Based Machine Learning in University
- (2020) Tran Anh Khoa et al. WIRELESS COMMUNICATIONS & MOBILE COMPUTING
- Biogas from food waste through anaerobic digestion: optimization with response surface methodology
- (2020) B. Deepanraj et al. Biomass Conversion and Biorefinery
- The world’s growing municipal solid waste: Trends and impacts
- (2020) David Meng-Chuen Chen et al. Environmental Research Letters
- Landfill area estimation based on solid waste collection prediction using ANN model and final waste disposal options
- (2020) Md. Maruful Hoque et al. JOURNAL OF CLEANER PRODUCTION
- New insights into regional differences of the predictions of municipal solid waste generation rates using artificial neural networks
- (2020) Fan Wu et al. WASTE MANAGEMENT
- Artificial intelligence applications in solid waste management: A systematic research review
- (2020) Mohamed Abdallah et al. WASTE MANAGEMENT
- Estimating Physical Composition of Municipal Solid Waste in China by Applying Artificial Neural Network Method
- (2020) Shijun Ma et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Application of artificial intelligence neural network modeling to predict the generation of domestic, commercial and construction wastes
- (2020) Gulnur Coskuner et al. WASTE MANAGEMENT & RESEARCH
- Exploring the ethical issues in research using digital data collection strategies with minors: A scoping review
- (2020) Danica Facca et al. PLoS One
- Application of machine learning methods for the prediction of organic solid waste treatment and recycling processes: A review
- (2020) Hao-nan Guo et al. BIORESOURCE TECHNOLOGY
- Machine learning based modelling for lower heating value prediction of municipal solid waste
- (2020) Cansu Birgen et al. FUEL
- Multi-task prediction and optimization of hydrochar properties from high-moisture municipal solid waste: Application of machine learning on waste-to-resource
- (2020) Jie Li et al. JOURNAL OF CLEANER PRODUCTION
- Detecting glass and metal in consumer trash bags during waste collection using convolutional neural networks
- (2020) Oliver Istad Funch et al. WASTE MANAGEMENT
- Application of an artificial intelligence technique enhanced with intelligent water drops for monthly reference evapotranspiration estimation
- (2020) Farshad Ahmadi et al. AGRICULTURAL WATER MANAGEMENT
- Forecasting municipal solid waste quantity using artificial neural network and supported vector machine techniques: A case study of Johannesburg, South Africa
- (2020) O.O. Ayeleru et al. JOURNAL OF CLEANER PRODUCTION
- Detection of long-term effect in forecasting municipal solid waste using a long short-term memory neural network
- (2020) Dongjie Niu et al. JOURNAL OF CLEANER PRODUCTION
- Comparative study of predicting hospital solid waste generation using multiple linear regression and artificial intelligence
- (2019) Somayeh Golbaz et al. Journal of Environmental Health Science and Engineering
- Solid waste management: Scope and the challenge of sustainability
- (2019) Subhasish Das et al. JOURNAL OF CLEANER PRODUCTION
- Municipal solid waste management with cost minimization and emission control objectives: A case study of Ankara
- (2019) Melika Mohsenizadeh et al. Sustainable Cities and Society
- Municipal solid waste (MSW) pyrolysis for bio-fuel production: A review of effects of MSW components and catalysts
- (2018) Ayesha Tariq Sipra et al. FUEL PROCESSING TECHNOLOGY
- Municipal solid waste generation in China: influencing factor analysis and multi-model forecasting
- (2018) Leaksmy Chhay et al. Journal of Material Cycles and Waste Management
- Modeling and prediction of regional municipal solid waste generation and diversion in Canada using machine learning approaches
- (2018) Miyuru Kannangara et al. WASTE MANAGEMENT
- Multi-response optimization of process parameters in biogas production from food waste using Taguchi – Grey relational analysis
- (2017) B. Deepanraj et al. ENERGY CONVERSION AND MANAGEMENT
- Effect of substrate pretreatment on biogas production through anaerobic digestion of food waste
- (2017) B. Deepanraj et al. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
- Waste to energy technologies for municipal solid waste management in Gaziantep
- (2016) Alperen Tozlu et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Forecasting municipal solid waste generation using artificial intelligence modelling approaches
- (2016) Maryam Abbasi et al. WASTE MANAGEMENT
- Prediction of municipal solid waste generation using nonlinear autoregressive network
- (2015) Mohammad K. Younes et al. ENVIRONMENTAL MONITORING AND ASSESSMENT
- Experimental and kinetic study on anaerobic digestion of food waste: The effect of total solids and pH
- (2015) B. Deepanraj et al. Journal of Renewable and Sustainable Energy
- Solid waste forecasting using modified ANFIS modeling
- (2015) Mohammad K. Younes et al. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION
- Artificial Intelligence-Based Techniques for Emerging Heterogeneous Network: State of the Arts, Opportunities, and Challenges
- (2015) Xiaofei Wang et al. IEEE Access
- An overview of characteristics of municipal solid waste fuel in China: Physical, chemical composition and heating value
- (2014) Hui Zhou et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Optimal process network for municipal solid waste management in Iskandar Malaysia
- (2013) Sie Ting Tan et al. JOURNAL OF CLEANER PRODUCTION
- Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier
- (2013) Md. Shafiqul Islam et al. WASTE MANAGEMENT
- A two-stage support-vector-regression optimization model for municipal solid waste management – A case study of Beijing, China
- (2011) C. Dai et al. JOURNAL OF ENVIRONMENTAL MANAGEMENT
- Application and evaluation of forecasting methods for municipal solid waste generation in an eastern-European city
- (2011) Ingrida Rimaitytė et al. WASTE MANAGEMENT & RESEARCH
- A system dynamic modeling approach for evaluating municipal solid waste generation, landfill capacity and related cost management issues
- (2010) Naushad Kollikkathara et al. WASTE MANAGEMENT
- Modelling municipal solid waste generation: A review
- (2007) Peter Beigl et al. WASTE MANAGEMENT
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started