A scientometrics review of soil properties prediction using soft computing approaches
In this world, several types of soils are available with their different engineering properties.
Determining each soil's engineering properties is difficult because the laboratory procedures …
Determining each soil's engineering properties is difficult because the laboratory procedures …
CBR of stabilized and reinforced residual soils using experimental, numerical, and machine-learning approaches
This research employed coir fiber and activated carbon as eco-friendly additives and waste
materials while using lime as a traditional binder to improve the properties of two residual …
materials while using lime as a traditional binder to improve the properties of two residual …
Hybrid soft computing models for predicting unconfined compressive strength of lime stabilized soil using strength property of virgin cohesive soil
This work introduces an optimal performance model for predicting the unconfined
compressive strength (UCS) of lime-stabilized soil using the machine (ensemble tree (ET) …
compressive strength (UCS) of lime-stabilized soil using the machine (ensemble tree (ET) …
Intelligent waste sorting for sustainable environment: A hybrid deep learning and transfer learning model
The significance of waste disposal, classification, and monitoring has dramatically increased
due to the increase in industrial development and the progress of intelligent urbanization …
due to the increase in industrial development and the progress of intelligent urbanization …
From waste to resource: Evaluating the possibility of incinerator bottom ash composites for geotechnical applications
The study targets the potential geotechnical applications of municipal solid waste incinerator
bottom ash (MSW-IBA) when reinforced with fiber. The mechanical performance of stabilized …
bottom ash (MSW-IBA) when reinforced with fiber. The mechanical performance of stabilized …
Intelligent mixture optimization for stabilized soil containing solid waste based on machine learning and evolutionary algorithms
J Wang, G Chen, Y Chen, Z Ye, M Lin, R Su… - Construction and Building …, 2024 - Elsevier
The usage of industrial solid waste to improve soil for road materials has attracted
widespread attention. In addition to mechanical performance, economic and environmental …
widespread attention. In addition to mechanical performance, economic and environmental …
Intelligent prediction method for underbreak extent in underground tunnelling
M Tao, Z Hong, H Zhao, M Zhao, D Wang - International Journal of Rock …, 2024 - Elsevier
Underground tunnel excavation using the drill-and-blast method often results in underbreak
occurrences due to improper blasting parameters and complex geological environment. This …
occurrences due to improper blasting parameters and complex geological environment. This …
Understanding municipal solid waste production and diversion factors utilizing deep-learning methods
Y Zhao, H Li - Utilities Policy, 2023 - Elsevier
We propose a hybrid deep learning neural network model for accurately calculating
municipal solid waste (MSW) production and diversions with socioeconomic and …
municipal solid waste (MSW) production and diversions with socioeconomic and …
Predictions of the key operating parameters in waste incineration using big data and a multiverse optimizer deep learning model
Z Zhao, Z Zhou, Y Lu, Z Li, Q Wei, H Xu - Sustainability, 2023 - mdpi.com
In order to accurately predict the key operating parameters of waste incinerators, this paper
proposes a prediction method based on big data and a Multi-Verse Optimizer deep learning …
proposes a prediction method based on big data and a Multi-Verse Optimizer deep learning …
Applying optimized machine learning models for predicting unconfined compressive strength in fine-grained soil
This research investigates the potential of optimized machine learning (OML) models for the
prediction of UCS in fine-grained soil. Leveraging OML models, the study makes use of an …
prediction of UCS in fine-grained soil. Leveraging OML models, the study makes use of an …