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A new hyperparameter to random forest: application of remote sensing in yield prediction
Since there has been concern about food security, accurate prediction of wheat yield prior to harvest is a key component. Random Forest (RF) has been...
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A comparative analysis of ensemble learning algorithms with hyperparameter optimization for soil liquefaction prediction
Accurate prediction of soil liquefaction potential is crucial for evaluating the stability of structures in earthquake regions. This study focuses on...
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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...
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Framework for Hyperparameter Impact Analysis and Selection for Water Resources Feedforward Neural Network
The Feedforward Neural Network (FNN) is currently commonly used in problems involving water resources. However, the hyperparameters have received...
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Assessing the predictive capability of DeepBoost machine learning algorithm powered by hyperparameter tuning methods for slope stability prediction
This paper presents DeepBoost based classification model for the slope stability problem, wherein an extensive dataset consisting of six features is...
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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...
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Hyperparameter tuning of supervised bagging ensemble machine learning model using Bayesian optimization for estimating stormwater quality
Physically based models (PBMs), including stormwater management model (SWMM), require a significant amount of in situ data and expertise to predict...
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Augmenting Stationary Covariance Functions with a Smoothness Hyperparameter and Improving Gaussian Process Regression Using a Structural Similarity Index
AbstractGaussian process (GP) regression provides a probabilistic framework for modeling geochemistry in mineral resource estimation and...
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Evaporation Prediction with Wavelet-Based Hyperparameter Optimized K-Nearest Neighbors and Extreme Gradient Boosting Algorithms in a Semi-Arid Environment
The study aims to reveal which mother wavelet type performs best in evaporation prediction. This study used a hybrid algorithm that combined...
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Rapid natural hazard extent estimation from twitter data: investigation for hurricane impact areas
Natural hazards have occurred more frequently in the past years and pose a severe risk to human life. Their extents and, thereby, the most heavily...
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Forest Aboveground Biomass and Forest Height Estimation Over a Sub-tropical Forest Using Machine Learning Algorithm and Synthetic Aperture Radar Data
Forest aboveground biomass (AGB) is a key measurement in studying terrestrial carbon storage, carbon cycle, and climate change. Machine learning...
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A Novel Hybrid Machine Learning Approach and Basin Modeling for Thermal Maturity Estimation of Source Rocks in Mandawa Basin, East Africa
Basin modeling and thermal maturity estimation are crucial for understanding sedimentary basin evolution and hydrocarbon potential. Assessing thermal...
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Automatic Estimation Of Rock Quality Designation Based On An Improved YOLOv5
Rock quality designation (RQD) characteristics for assessing the degree of rock mass fracture make it a key parameter in rock grading or other rating...
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Total organic carbon (TOC) estimation using ensemble and artificial neural network methods; a case study from Kazhdumi Formation, NW Persian Gulf
Total Organic Carbon (TOC) is one of the most important geochemical parameters in source rock evaluation, utilized to characterize the hydrocarbon...
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Rainfall Forecasting using a Bayesian framework and Long Short-Term Memory Multi-model Estimation based on an hourly meteorological monitoring network. Case of study: Andean Ecuadorian Tropical City
Rainfall forecasting is a challenging task due to the time-dependencies of the variables and the stochastic behavior of the process. The difficulty...
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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...
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Real-time earthquake magnitude estimation via a deep learning network based on waveform and text mixed modal
Rapid and accurate earthquake magnitude estimations are essential for earthquake early warning (EEW) systems. The distance information between the...
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Machine learning techniques in estimation of eggplant crop evapotranspiration
This study predicted the daily evapotranspiration of eggplant ( Solanum melongena L.) under full and deficit irrigation in the Bafra district of...
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Machine learning model for snow depth estimation using a multisensory ubiquitous platform
Snow depth estimation is an important parameter that guides several hydrological applications and climate change prediction. Despite advances in...
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An ensemble deep learning approach for air quality estimation in Delhi, India
South Asian megacities, notably Delhi, are significant contributors to air pollution, driven by factors such as population density, vehicular...
