Search
Search Results
-
Analysis of the hyperparameter optimisation of four machine learning satellite imagery classification methods
The classification of land use and land cover (LULC) from remotely sensed imagery in semi-arid Mediterranean areas is a challenging task due to the...
-
Prediction of karst spring discharge using LSTM with Bayesian optimisation hyperparameter tuning: a laboratory physical model approach
Estimating spring discharge in karst aquifers is challenging due to non-linear and non-stationary hydrological processes caused by spatial and...
-
Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models
Evolutionary algorithms provide gradient-free optimisation which is beneficial for models that have difficulty in obtaining gradients; for instance,...
-
Microseismicity-based short-term rockburst prediction using non-linear support vector machine
Microseismic (MS) monitoring is a short-term rockburst prediction technique that foretells the source, time and damage scale inside a rock mass...
-
Enhanced Daily Reference Evapotranspiration Estimation Using Optimized Hybrid Support Vector Regression Models
Accurate estimation of reference evapotranspiration (ET 0 ) is a crucial parameter in implementing precise irrigation strategies and managing regional...
-
Evaluating landslide susceptibility and landscape changes due to road expansion using optimized machine learning
The Garhwal and Kumaun regions of the Himalayas of India have experienced rapid urbanisation due to the expansion of the national highway (NH-58) in...
-
Rock recognition and identification for selective mechanical mining: a self-adaptive artificial neural network approach
In situ characterisation of rock is crucial for mine planning and design. Recent developments in machine learning (ML) have enabled the whole...
-
A hybrid of RainNet and genetic algorithm in nowcasting prediction
Quantitative precipitation nowcasting QPN is a powerful tool with many applications, such as rainfall prediction, urban sewage control, etc....
-
Machine learning assisted lithology prediction using geophysical logs: A case study from Cambay basin
AbstractIdentification and characterisation of reservoir facies is a prime factor in delimiting the hydrocarbon potential zones of a reservoir for...
-
Parametric evaluation and prediction of design parameters of geofoam using artificial neural network and extreme gradient boosting models
Expanded polystyrene (EPS) geofoam is increasingly used in the construction industry as a lightweight fill material. The selection of an appropriate...
-
A novel application of transformer neural network (TNN) for estimating pan evaporation rate
For decision-making in farming, the operation of dams and irrigation systems, as well as other fields of water resource management and hydrology,...
-
Quantifying 3D and suction-induced effects on soil slope stability during rapid drawdown: a sensitivity study using the MARS-WOA approach
The study presents a new hybrid model, called MARS-WOA, which predicts the impact of three-dimensional (3D) and suction-induced effects on soil slope...
-
A Comprehensive Review on Map** of Groundwater Potential Zones: Past, Present and Future Recommendations
The over exploitation of groundwater resources is a highly thought-provoking issue, which hinders the goal of sustainable water management worldwide....
-
A comparative analysis of machine learning algorithms for predicting wave runup
The present study uses nine machine learning (ML) methods to predict wave runup in an innovative and comprehensive methodology. Unlike previous...
-
Shapelet-informed machine learning classifiers: A path towards precise identification of pulse-like ground motions
The accurate identification of pulse-like ground motions for utilisation by engineers continues to remain a challenge since the existing techniques...
-
Application of XGBoost model for early prediction of earthquake magnitude from waveform data
In this paper, a scalable end-to-end tree boosting system called XGBoost has been applied for predicting the magnitude of an earthquake from the...
-
Application of hybrid model-based machine learning for groundwater potential prediction in the north central of Vietnam
Groundwater resources are required for domestic water supply, agriculture, and industry, and the strategic importance of water resources will only...
-
Anomaly detection method for TBM construction based on improved VMD-XGBoost-BILSTM combined model
TBM method construction is an important accompanying construction form vigorously developed in China, and its anomaly detection is an important link...
-
Prediction and validation of geogrid tensile force distribution in back-to-back MSE walls under rail axle load: finite-element and intelligent techniques
In this study, an investigation was conducted to assess the performance of artificial intelligence (AI) and machine learning (ML) methods with...
-
Coseismic Landslide Susceptibility and Triggering Analyses
This chapter reviews the methods used to carry out coseismic landslide susceptibility and slope stability analyses, from the regional- to the...