Results 111 to 120 of about 13,817,849 (263)
Reconnaissance‐Scale Methods for the Identification of Groundwater Discharge to Streams
Groundwater Monitoring &Remediation, EarlyView.Abstract Identifying groundwater discharge locations is critical for understanding and monitoring groundwater contributions to streams in terms of water quantity and quality. Streams and rivers are under increasing strain from factors, including increased urbanization, agricultural land use, groundwater extraction, and climate change, which can alter ...
Corey M. Zanatta +2 more
wiley +1 more source
Benchmarking Knowledge-assisted Kriging for Automated Spatial Interpolation of Wind Measurements
- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of spatial cohesion to be specified and variograms calculated for each region.
Zlatev, Zlatko +2 more
core +1 more source
Combining the Finite Element Analysis and Kriging Model for Study on Laser Surface Hardening Parameters of Pitch Bearing Raceway. [PDF]
Materials (Basel), 2022 Zhang H, Zhu M, Ji S, Dou Y.
europepmc +1 more source
Adaptive Weighted Expected Improvement With Rewards Approach in Kriging Assisted Electromagnetic Design [PDF]
, 2013 The paper explores kriging surrogate modelling combined with expected improvement approach for the design of electromagnetic devices. A novel algorithm based on the concept of rewards is proposed, tested and demonstrated in the context of TEAM Workshop ...
Rotaru, M., Sykulski, J.K., Xiao, Song
core +1 more source
Groundwater Monitoring &Remediation, EarlyView.Abstract The long‐term and frequent sampling of groundwater monitoring networks is common practice for monitoring the concentrations of constituents of potential concern (CoPC) over space and time. Sampling can be a costly and time‐intensive process that also incurs health and safety risks. A redundancy‐based ranking of candidate sampling locations can
Peter Radvanyi +5 more
wiley +1 more source
On Spatial Point Processes With Composition‐Valued Marks
International Statistical Review, EarlyView.Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed ...
Matthias Eckardt +2 more
wiley +1 more source
, 2006 A novel kriging-assisted algorithm is proposed for computationally expensive single-objective optimization. The principle behind the algorithm is to use information about objective function space at the earliest possible opportunity. After constructing a
Hawe, G. I., Sykulski, J. K.
core +2 more sources
A Penalized Orthogonal Kriging Method for Selecting a Global Trend
AxiomsA 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 ...
Xituo Zhang +3 more
doaj +1 more source
Customized Sequential Designs for Random Simulation Experiments: Kriging Metamodelling and Bootstrapping [PDF]
This paper proposes a novel method to select an experimental design for interpolation in random simulation.(Though the paper focuses on Kriging, this method may also apply to other types of metamodels such as linear regression models.)Assuming that ...
Kleijnen, J.P.C., Beers, W.C.M. van
core
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
International Statistical Review, EarlyView.Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source