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Modeling spatial distribution of earthquake epicenters using inhomogeneous Log-Gaussian Cox point process
This paper explores the applicability of Inhomogeneous Log-Gaussian Cox point process to a complex spatial mechanism generating the tightly clustered...
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Regional storm surge hazard quantification using Gaussian process metamodeling techniques
The recent, very active hurricane seasons, as well as emerging concerns related to the future effects of sea-level rise, hurricane intensification,...
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Reservoir porosity assessment and anomaly identification from seismic attributes using Gaussian process machine learning
Porosity, as one of the reservoir properties, is an important parameter to numerous studies, i.e., the reservoir’s oil/gas volume estimation or even...
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Probabilistic Back Analysis Based on Nadam, Bayesian, and Matrix-Variate Deep Gaussian Process for Rock Tunnels
Efficiently determining the properties of the rock mass is essential for evaluating tunnel stability in tunneling projects. The back-analysis...
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Geostatistical modelling of rainfall in Fars Province of Iran using non-Gaussian spatial process
Prediction of response values is a primary goal in many applications. The standard approach to this problem is kriging which is essentially a linear...
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Prediction of soil compaction parameters through the development and experimental validation of Gaussian process regression models
The laboratory determination of maximum dry density ( ρ dmax ) and optimum moisture content ( w opt ) of soils requires considerable time and energy....
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Probabilistic Back Analysis Based on Adam, Bayesian and Multi-output Gaussian Process for Deep Soft-Rock Tunnel
The uncertainty of surrounding rock mechanical parameters has much great influence on design, construction and stability evaluation for tunnel...
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Reconstruction of geodetic time series with missing data and time-varying seasonal signals using Gaussian process for machine learning
Seasonal signals in satellite geodesy time series are mainly derived from a number of loading sources, such as atmospheric pressure and hydrological...
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Resilience-based seismic design optimization of novel link beam in a double-column bridge bent using Gaussian process regression
For bridge columns with link beams, the traditional reinforced concrete beam-column joints are susceptible to damage in near-fault ground motions,...
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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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Convolutional Neural Network -Support Vector Machine Model-Gaussian Process Regression: A New Machine Model for Predicting Monthly and Daily Rainfall
Rainfall prediction is an important issue in water resource management. Predicting rainfall helps researchers to monitor droughts, surface water and...
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Predicting Hydropower Production Using Deep Learning CNN-ANN Hybridized with Gaussian Process Regression and Salp Algorithm
The hydropower industry is one of the most important sources of clean energy. Predicting hydropower production is essential for the hydropower...
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Bias adjustment of satellite rainfall data through Gaussian process regression (GPR) based on rain intensity classification in the Greater Bay Area, China
Estimating precipitation over large spatial areas remains a challenging problem for hydrologists. Satellite-based remote sensing rainfall products...
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Non-Gaussian Ensemble Optimization
Ensemble-based optimization (EnOpt), commonly used in reservoir management, can be seen as a special case of a natural evolution algorithm. Stein’s...
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A Gaussian process regression-based sea surface temperature interpolation algorithm
The resolution of ocean reanalysis datasets is generally low because of the limited resolution of their associated numerical models. Low-resolution...
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Prediction of Uniaxial Compressive Strength Using Fully Bayesian Gaussian Process Regression (fB-GPR) with Model Class Selection
In rock, mining, and/or tunneling engineering, determination of uniaxial compressive strength (UCS) of rocks is an important and crucial task, which...
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A GNSS interference source tracking method using the continuous-discrete Gaussian kernel quadrature Kalman filter
Global Navigation Satellite Systems (GNSSs) are vulnerable to interference due to low satellite signal transmission power, and thus the problem of...
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Groundwater level estimation in northern region of Bangladesh using hybrid locally weighted linear regression and Gaussian process regression modeling
Urban groundwater resources (GWRs) have declined substantially in recent decades, due to rapid urbanization, population growth, groundwater...
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Statistical characterization of full-margin rupture recurrence for Cascadia subduction zone using event time resampling and Gaussian mixture model
Earthquake occurrence modeling of large subduction events involves significant uncertainty, stemming from the scarcity of geological data and...
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Comparison of the Performance of a Surrogate Based Gaussian Process, NSGA2 and PSO Multi-objective Optimization of the Operation and Fuzzy Structural Reliability of Water Distribution System: Case Study for the City of Asmara, Eritrea
Optimal scheduling of pumps in water distribution systems (WDSs) entails reducing operational cost while supplying the required water quality and...
