Research graph
References from Artificial intelligence and machine learning in sustainable sand production. Local targets link to admitted publications; unresolved targets remain external evidence.
Recent trends in wind energy conversion system with grid integration based on soft computing methods: comprehensive review, comparisons and insights
10.1007/s11831-022-09842-4 · 2023 · External reference
River sand characterization for its use in concrete: a revue
10.4236/ojce.2023.132027 · 2023 · External reference
Chapter 9—machine learning applications for developing sustainable construction materials
2022 · External reference
Evaluation of sisal fiber and aluminum waste concrete blend for sustainable construction using adaptive neuro-fuzzy inference system
10.1038/s41598-023-30008-0 · 2023 · External reference
Mechanical performance and feasibility analysis of green concrete prepared with local natural zeolite and waste PET plastic fibers as cement replacements
2022 · External reference
Incorporation of recycled aggregates and silica fume in concrete: an environmental savior-a systematic review
10.1016/j.jmrt.2022.09.021 · 2022 · External reference
Suitability of sustainable sand for concrete manufacturing - a complete review of recycled and desert sand substitution
10.1016/j.rineng.2024.102478 · 2024 · External reference
River sand replacement with sustainable sand in design mix concrete for the construction industry
10.28991/cej-2025-011-01-012 · 2025 · External reference
An interpretable XGBoost-SHAP machine learning model for reliable prediction of mechanical properties in waste foundry sand-based eco-friendly concrete
10.1016/j.rineng.2025.104307 · 2025 · External reference
Development of prediction models for interlayer shear strength in asphalt pavement using machine learning and SHAP techniques
10.1080/14680629.2023.2276412 · 2024 · External reference
Structural design analysis of hybrid multirise buildings, with CLT and LGS light weight floor system, at Neom-The Line
10.21741/9781644903414-12 · 2025 · External reference
High-performance self-compacting concrete with recycled coarse aggregate: soft-computing analysis of compressive strength
2023 · External reference
Experimental investigation of sand-based sensible heat energy storage system
10.1016/j.applthermaleng.2024.125390 · 2025 · External reference
Mechanisms of sand production, prediction–a review and the potential for fiber optic technology and machine learning in monitoring
10.1007/s13202-024-01860-1 · 2024 · External reference
Soft computing solutions for reducing the carbon footprint of fly ash based concrete
2025 · External reference
The complexity of sand mining in coastal regions of India: implications on livelihoods, marine and riverine environment, sustainable development, and governance
10.54007/ijmaf.2023.e3 · 2023 · External reference
Assessing riverbank change caused by sand mining and waste disposal using web-based volunteered geographic information
10.3390/w16050734 · 2024 · External reference
The way forward to sustain environmental quality through sustainable sand mining and the use of manufactured sand as an alternative to natural sand
10.1007/s11356-022-19633-w · 2022 · External reference
Application of machine learning in predicting mechanical properties of sandcrete blocks made from quarry dust: a review
10.1007/s43503-024-00033-7 · 2024 · External reference
Design of experiment on concrete mechanical properties prediction: a critical review
10.3390/ma14081866 · 2021 · External reference
Artificial intelligence in supply chain management: a systematic literature review of empirical studies and research directions
10.1016/j.compind.2024.104132 · 2024 · External reference
Sand mining in BRICS economies: tragedy of the commons or fortune in the making?
10.1016/j.jclepro.2023.140122 · 2024 · External reference
Advances in application of machine learning to life cycle assessment: a literature review
10.1007/s11367-022-02030-3 · 2022 · External reference
Regulatory and policy implications of sand mining along shallow waters of Njelele River in South Africa
2019 · External reference
Predicting compressive strength of eco-friendly plastic sand paver blocks using gene expression and artificial intelligence programming
10.1038/s41598-023-39349-2 · 2023 · External reference
Comparative analysis of various machine learning algorithms to predict strength properties of sustainable green concrete containing waste foundry sand
10.1038/s41598-024-65255-2 · 2024 · External reference
The effect of geopolymer slurries with clinker aggregates and marble waste powder on embodied energy and high-temperature resistance in prepacked concrete: ANFIS-based prediction model
2023 · External reference
A novel approach to sand production prediction using artificial intelligence
10.1016/j.petrol.2014.07.033 · 2014 · External reference
A predictive maintenance system for multigranularity faults based on AdaBelief-BP neural network and fuzzy decision making
10.1016/j.aei.2021.101318 · 2021 · External reference
A comprehensive review on computing methods for the prediction of energy cost in Kingdom of Saudi Arabia
10.21741/9781644903216-21 · 2024 · External reference
Analyzing the differences between the impacts of wind and earthquakes on base shear and drift in diagrid structures
10.21741/9781644903414-2 · 2025 · External reference
Optimizing cover concrete durability in ready mixed concrete a critical review of curing methods and their impact on performance
10.21741/9781644903414-31 · 2025 · External reference
Machine learning and RSM-CCD analysis of green concrete made from waste water plastic bottle caps: towards performance and optimization
2023 · External reference
Machine learning models for predicting the compressive strength of concrete with shredded PET bottles and M-sand as fine aggregate
10.31436/iiumej.v26i1.2998 · 2025 · External reference
Unresolved reference
2023 · External reference
Evaluation of machine-learning tools for predicting sand production
2021 · External reference
AI mix design of fly ash admixed concrete based on mechanical and environmental impact considerations
10.28991/cej-sp2023-09-03 · 2023 · External reference
The global impact of sand mining on beaches and dunes
10.1016/j.ocecoaman.2023.106492 · 2023 · External reference
Experimental analysis and gene expression programming optimization of sustainable concrete containing mineral fillers
10.1038/s41598-024-79314-1 · 2024 · External reference
The environmental impacts of river sand mining
2022 · External reference
A systematic review of machine learning techniques and applications in soil improvement using green materials
10.3390/su15129738 · 2023 · External reference
The sand curse: sand mining, environmental degradation and social conflicts in the Gambia
10.1016/j.worlddev.2025.107125 · 2025 · External reference
Role of artificial intelligence (AI) and machine learning (ML) in the corrosion monitoring processes
10.62638/zasmat1192 · 2024 · External reference
Machine learning applications for precision agriculture: a comprehensive review
10.1109/access.2020.3048415 · 2021 · External reference
Application of machine learning and artificial intelligence in oil and gas industry
10.1016/j.ptlrs.2021.05.009 · 2021 · External reference
Comparison of machine learning algorithms for sand production prediction: an example for a gas-hydrate-bearing sand case
10.3390/en15186509 · 2022 · External reference
Implementation of soft computing techniques in forecasting compressive strength and permeability of pervious concrete blended with ground granulated blast-furnace slag
2024 · External reference
Advancements and challenges in machine learning: a comprehensive review of models, libraries, applications, and algorithms
10.3390/electronics12081789 · 2023 · External reference
Artificial intelligence and machine learning for sustainable manufacturing: current trends and future prospects
2025 · External reference
Sand production during hydrocarbon exploitation: mechanisms, factors, prediction, and perspectives
10.1016/j.geoen.2025.213954 · 2025 · External reference
Impact assessment of river sand resource shortage under different policy scenarios in China
10.1007/s44242-023-00015-5 · 2023 · External reference
Towards sustainable governance of freshwater sand – a resource regime approach
2024 · External reference
The way forward to sustain environmental quality through sustainable sand mining and the use of manufactured sand as an alternative to natural sand
10.1007/s11356-022-19633-w · ExternalCitation · doi-reference
Advances in application of machine learning to life cycle assessment: a literature review
10.1007/s11367-022-02030-3 · ExternalCitation · doi-reference
Recent trends in wind energy conversion system with grid integration based on soft computing methods: comprehensive review, comparisons and insights
10.1007/s11831-022-09842-4 · ExternalCitation · doi-reference
Mechanisms of sand production, prediction–a review and the potential for fiber optic technology and machine learning in monitoring
10.1007/s13202-024-01860-1 · ExternalCitation · doi-reference
Application of machine learning in predicting mechanical properties of sandcrete blocks made from quarry dust: a review
10.1007/s43503-024-00033-7 · ExternalCitation · doi-reference
Impact assessment of river sand resource shortage under different policy scenarios in China
10.1007/s44242-023-00015-5 · ExternalCitation · doi-reference
A predictive maintenance system for multigranularity faults based on AdaBelief-BP neural network and fuzzy decision making
10.1016/j.aei.2021.101318 · ExternalCitation · doi-reference
Experimental investigation of sand-based sensible heat energy storage system
10.1016/j.applthermaleng.2024.125390 · ExternalCitation · doi-reference
Artificial intelligence in supply chain management: a systematic literature review of empirical studies and research directions
10.1016/j.compind.2024.104132 · ExternalCitation · doi-reference
Sand production during hydrocarbon exploitation: mechanisms, factors, prediction, and perspectives
10.1016/j.geoen.2025.213954 · ExternalCitation · doi-reference
Sand mining in BRICS economies: tragedy of the commons or fortune in the making?
10.1016/j.jclepro.2023.140122 · ExternalCitation · doi-reference
Incorporation of recycled aggregates and silica fume in concrete: an environmental savior-a systematic review
10.1016/j.jmrt.2022.09.021 · ExternalCitation · doi-reference
The global impact of sand mining on beaches and dunes
10.1016/j.ocecoaman.2023.106492 · ExternalCitation · doi-reference
A novel approach to sand production prediction using artificial intelligence
10.1016/j.petrol.2014.07.033 · ExternalCitation · doi-reference
Application of machine learning and artificial intelligence in oil and gas industry
10.1016/j.ptlrs.2021.05.009 · ExternalCitation · doi-reference
Suitability of sustainable sand for concrete manufacturing - a complete review of recycled and desert sand substitution
10.1016/j.rineng.2024.102478 · ExternalCitation · doi-reference
An interpretable XGBoost-SHAP machine learning model for reliable prediction of mechanical properties in waste foundry sand-based eco-friendly concrete
10.1016/j.rineng.2025.104307 · ExternalCitation · doi-reference
The sand curse: sand mining, environmental degradation and social conflicts in the Gambia
10.1016/j.worlddev.2025.107125 · ExternalCitation · doi-reference
Evaluation of sisal fiber and aluminum waste concrete blend for sustainable construction using adaptive neuro-fuzzy inference system
10.1038/s41598-023-30008-0 · ExternalCitation · doi-reference
Predicting compressive strength of eco-friendly plastic sand paver blocks using gene expression and artificial intelligence programming
10.1038/s41598-023-39349-2 · ExternalCitation · doi-reference
Comparative analysis of various machine learning algorithms to predict strength properties of sustainable green concrete containing waste foundry sand
10.1038/s41598-024-65255-2 · ExternalCitation · doi-reference
Experimental analysis and gene expression programming optimization of sustainable concrete containing mineral fillers
10.1038/s41598-024-79314-1 · ExternalCitation · doi-reference
Development of prediction models for interlayer shear strength in asphalt pavement using machine learning and SHAP techniques
10.1080/14680629.2023.2276412 · ExternalCitation · doi-reference
Machine learning applications for precision agriculture: a comprehensive review
10.1109/access.2020.3048415 · ExternalCitation · doi-reference
A comprehensive review on computing methods for the prediction of energy cost in Kingdom of Saudi Arabia
10.21741/9781644903216-21 · ExternalCitation · doi-reference
Structural design analysis of hybrid multirise buildings, with CLT and LGS light weight floor system, at Neom-The Line
10.21741/9781644903414-12 · ExternalCitation · doi-reference
Analyzing the differences between the impacts of wind and earthquakes on base shear and drift in diagrid structures
10.21741/9781644903414-2 · ExternalCitation · doi-reference
Optimizing cover concrete durability in ready mixed concrete a critical review of curing methods and their impact on performance
10.21741/9781644903414-31 · ExternalCitation · doi-reference
River sand replacement with sustainable sand in design mix concrete for the construction industry
10.28991/cej-2025-011-01-012 · ExternalCitation · doi-reference
AI mix design of fly ash admixed concrete based on mechanical and environmental impact considerations
10.28991/cej-sp2023-09-03 · ExternalCitation · doi-reference
Machine learning models for predicting the compressive strength of concrete with shredded PET bottles and M-sand as fine aggregate
10.31436/iiumej.v26i1.2998 · ExternalCitation · doi-reference
Advancements and challenges in machine learning: a comprehensive review of models, libraries, applications, and algorithms
10.3390/electronics12081789 · ExternalCitation · doi-reference
Comparison of machine learning algorithms for sand production prediction: an example for a gas-hydrate-bearing sand case
10.3390/en15186509 · ExternalCitation · doi-reference
Design of experiment on concrete mechanical properties prediction: a critical review
10.3390/ma14081866 · ExternalCitation · doi-reference
A systematic review of machine learning techniques and applications in soil improvement using green materials
10.3390/su15129738 · ExternalCitation · doi-reference
Assessing riverbank change caused by sand mining and waste disposal using web-based volunteered geographic information
10.3390/w16050734 · ExternalCitation · doi-reference
River sand characterization for its use in concrete: a revue
10.4236/ojce.2023.132027 · ExternalCitation · doi-reference
The complexity of sand mining in coastal regions of India: implications on livelihoods, marine and riverine environment, sustainable development, and governance
10.54007/ijmaf.2023.e3 · ExternalCitation · doi-reference
Role of artificial intelligence (AI) and machine learning (ML) in the corrosion monitoring processes
10.62638/zasmat1192 · ExternalCitation · doi-reference
