Results 81 to 90 of about 77,394 (227)
SPASIAL DATA MINING MENGGUNAKAN MODEL SAR-KRIGING
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 The region of Indonesia is very sparse and it has a variation condition in social, economic and culture, so the problem in education quality at many locations is an interesting topic to be studied.
Atje Setiawan, Rudi Rosadi
doaj +1 more source
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
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingAccuracy of radar interferometry is often hindered by the atmospheric phase screen (APS). To address this limitation, the geostatistical approach known as Kriging has been employed to predict APS from sparse observations for compensation purposes.
Yuta Izumi +5 more
doaj +1 more source
Calculation of Probability Maps Directly from Ordinary Kriging Weights [PDF]
Geologia USP. Série Científica, 2010 Probability maps are useful to analyze ores or contaminants in soils and they are helpful to make a decision duringexploration work. These probability maps are usually derived from the indicator kriging approach.
Jorge Kazuo Yamamoto
doaj
Shock and Vibration, 2016 This study focuses on the kriging based metamodeling for the prediction of parameter-dependent mode coupling instabilities. The high cost of the currently used parameter-dependent Complex Eigenvalue Analysis (CEA) has induced a growing need for ...
E. Denimal +3 more
doaj +1 more source
Ordinary kriging for on-demand average wind interpolation of in-situ wind sensor data
, 2009 We have developed a domain agnostic ordinary kriging algorithm accessible via a standards-based service-oriented architecture for sensor networks. We exploit the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards.
Middleton, S.E., Veres, G., Zlatev, Z.
core
Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
Journal of Economic Surveys, EarlyView.ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen +4 more
wiley +1 more source
Applied Sciences, 2019 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 highly
Jiajia Shi +2 more
doaj +1 more source
, 2007 The high computational cost of evaluating objective functions in electromagnetic optimal design problems necessitates the use of cost-effective techniques.
Hawe, G., Sykulski, J.K.
core
Comparison of Gaussian process modeling software [PDF]
, 2016 Gaussian process fitting, or kriging, is often used to create a model from a set of data. Many available software packages do this, but we show that very different results can be obtained from different packages even when using the same data and model ...
Ankenman, Bruce E. +2 more
core +2 more sources