In seismic exploration, establishing a reliable parameter model (such as velocity, density, impedance) is crucial for seismic migration imaging and reservoir characterization. The interpolation of well data to obtain a complete spatial model is an im...
Research on spatio-temporal geostatistical modeling remains a critical challenge in numerous scientific and engineering disciplines. This paper introduces a novel extension of dual kriging, called spatio-temporal dual kriging (ST-DK), in which drift...
Soil property maps are essential resources for agricultural land use. However, soil properties mapping is costly and time-consuming, especially in the regions with complicated topographic conditions. This study was conducted in a hilly region of Cent...
Volcanic eruptions significantly impact human life. However, real-time high-precision imaging in this context still has limitations. Spatial–temporal interpolation can replace real-time data imaging, in order to obtain the state of a given volc...
This paper presents a Kriging interpolation method for constructing a database of atmospheric refractivity in Korea. To collect as much data as possible for the interpolation, meteorological data from 120 regions of Korea, including both land and sea...
Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the iono...
A kriging regression model is a popular and effective type of surrogate model in computer experiments. A significant challenge arises when the mean function of the model includes polynomial terms with unknown coefficients, leading to identifiability...
Sampling and estimation of geographical attributes that vary across space (e.g., area temperature, urban pollution level, provincial cultivated land, regional population mortality and state agricultural production) are common yet important constituen...
In the study of spatiotemporal geographical phenomena, the space–time interpolation method is widely applied, and the demands for computing speed and accuracy are increasing. For nonprofessional modelers, utilizing the space–time interpol...
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AM...
The integration of active learning methods and multi-fidelity (MF) Kriging models has been demonstrated to effectively reduce the number of high-fidelity (HF) samples required for reliability analysis. However, there is a lack of comparative research...
A kriging modeling method is proposed to conduct the temperature uncertainty analysis of an injection mechanism in squeeze casting. A mathematical model of temperature prediction with multi input and single output is employed to estimate the temperat...
This contribution implements the Kriging interpolation in predicting the tropospheric wet delays using global navigation satellite system networks. The predicted tropospheric delays can be used in strengthening the precise point positioning models an...
Flight load calculation, an important step in aircraft design and optimization, typically involves millions of computations and requires significant computing resources and time. Improving the efficiency of flight load calculations while maintaining...
The super-resolution of depth images is a research hotspot. In this study, the classical Kriging algorithm is applied to the spatial interpolation of depth images, together with the fractional-order differential method for edge recognition, to realis...
The Kriging surrogate model in complex simulation problems uses as few expensive objectives as possible to establish a global or local approximate interpolation. However, due to the inversion of the covariance correlation matrix and the solving of Kr...
This study evaluates the effect of considering data intermittency and log-normality in applications of simple Kriging. Several sets of synthetic data, both intermittent and log-normal, were prepared for this purpose, and then four different Kriging a...
Surrogate modeling techniques are widely employed in solving constrained expensive black-box optimization problems. Therein, Kriging is among the most popular surrogates in which the trend function is considered as a constant mean. However, it also e...
Finding new valuable sampling points and making these points better distributed in the design space is the key to determining the approximate effect of Kriging. To this end, a high-precision Kriging modeling method based on hybrid sampling criteria (...
The calculation of tooth wear under mixed elastohydrodynamic lubrication is very complex and requires consideration of many conditions such as load distribution in the tooth meshing zone, micro-convex elastoplastic deformation and tooth surface tempe...
The numerical simulation of the optimal design of gravity dams is computationally expensive. Therefore, a new optimization procedure is presented in this study to reduce the computational cost for determining the optimal shape of a gravity dam. Optim...
The cone penetrometer test (CPT) has been widely used in geotechnical investigations. However, how to use the limited CPT data to reasonably predict the soil parameters of the unsampled regions remains a challenge. In the present study, we adopted th...
The integration of renewable generation adds complexity to the operation of the power system due to its unpredictable characteristics. Therefore, the development of methods to accurately model the uncertainty is necessary. In this paper, the spatio-t...
Integrating spatio-temporal kriging with machine learning improves estimation accuracy by addressing complex spatial and temporal variations in spatio-temporal phenomena. The improvement can be attributed to the enhanced flexibility of machine learni...
The utilization of modal frequency sensors is a feasible and effective way to monitor the settlement problem of the transmission tower foundation. However, the uncertainties and interference in the real operation environment of transmission towers hi...
In this paper, subdivided kriging multi-objective optimization (SKMOO) is proposed for the optimal design of interior permanent magnet synchronous motor (IPMSM). The SKMOO with surrogate kriging model can obtain a uniform and accurate pareto front se...
Jet pump efficiency heavily relies on the geometrical parameters of the pump design and parameter global optimization in the full variable space is still a big challenge. This paper proposed a global optimization method for annular jet pump design co...
In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory...
Kriging-based modeling has been widely used in computationally intensive simulations. However, the Kriging modeling of high-dimensional problems not only takes more time, but also leads to the failure of model construction. To this end, a Kriging mod...
To achieve the low-cycle fatigue (LCF) lifetime prediction and reliability estimation of turbine blisks, a Marine Predators Algorithm (MPA)-based Kriging (MPA-Kriging) method is developed by introducing the MPA into the Kriging model. To obtain the o...
Analyzing geological profiles is of great importance for various applications such as natural resource management, environmental assessment, and mining engineering projects. This study presents a novel geostatistical approach for subsurface geologica...
The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neigh...
In order to enhance the hydraulic performance of the volute pump, the Kriging model and genetic algorithm (GA) were used to optimize the 3D diffuser of the volute pump, and the hydraulic performance of the optimized model was compared and analyzed wi...
A Bayesian framework-based approach is proposed for the quantitative validation and calibration of the kriging metamodel established by simulation and experimental training samples of the injection mechanism in squeeze casting. The temperature data u...
The main approach for a Wi-Fi indoor positioning system is based on the received signal strength (RSS) measurements, and the fingerprinting method is utilized to determine the user position by matching the RSS values with the pre-surveyed RSS databas...
This study proposed a Kriging surrogate model incorporating active learning to overcome the high computational costs associated with conducting reliability and sensitivity analyses of industrial liquid storage tank structures. In the proposed method,...
Due to the inevitable presence of random defects, unpredictable grain boundaries in macroscopic samples, stress concentration at clamping points, and unknown load distribution in the investigation of graphene sheets, uncertainties are crucial and cha...
Wireless sensor systems often fail to provide measurements with uniform time spacing. Measurements can be delayed or even miss completely. Resampling to uniform intervals is necessary to satisfy the requirements of subsequent signal processing. Commo...
The turbine rotor is a core component in many energy conversion systems, where it is subjected to loads such as aerodynamic and centrifugal forces that make it highly susceptible to damage. Consequently, the reliability of the turbine rotor ranks amo...
Winter conditions create hazardous roads that municipalities work hard to maintain to ensure the safety of the travelling public. Targeting their efforts with effective network screening will help transportation managers address these problems. In ou...
This paper presents a proposed LSTM-based vertical-gradient prediction combined with three-dimensional kriging that enables reconstruction of greenhouse 3D temperature fields under sparse-sensor deployments while capturing temporal dynamics and spati...
The kriging optimization method that can only obtain one sampling point per cycle has encountered a bottleneck in practical engineering applications. How to find a suitable optimization method to generate multiple sampling points at a time while impr...
Upscaling in situ soil moisture observations (ISMO) to multiscale pixel estimations with kriging is a key step in the comprehensive usage of ISMO and remote sensing (RS) soil moisture data. Scale effects occur and introduce uncertainties during upsca...
In this paper, an uncertainty optimization method based on the adaptive hybrid correlation Kriging surrogate model is proposed to optimize the ply angles of laminated spherical-conical shells. First, equations of motion of laminated spherical-conical...
The forest area in China’s plateaus and mountainous regions accounts for as much as 43% of the country’s total forest area. Accurately estimating the aboveground biomass (AGB) in these plateau and mountain forests is significant for globa...
The computational complexity of airfoil optimization for aircraft wing designs typically involves high-dimensional parameter spaces defined by geometric variables, where each Computational Fluid Dynamics (CFD) simulation cycle may require significant...
Airborne LiDAR scanning is a promising approach to providing high-resolution products that are appropriate for different applications, such as flood management. However, the vertical accuracy of airborne LiDAR point clouds is not constant and varies...
The adaptive Kriging method is widely used in the engineering design for complex black-box problems, yet its accuracy is limited by imbalanced exploitation–exploration. This paper proposes a KNN-based maximization of the weighted expected predi...
Mineral grade estimation is a vital phase in mine planning and design, as well as in the mining project’s economic assessment. In mining, commonly accepted methods of ore grade estimation include geometrical approaches and geostatistical techni...
An investigation on the flutter derivative prediction of flat steel box girders is carried out based on CFD simulations. Firstly, by taking the flat steel girder section of Qingshan Yangtze River Bridge as the basic section and considering its width...
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