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Gaussian Process Regression Reviewed in the Context of Inverse Theory
AbstractWe review Gaussian process regression (GPR) and analyze it in the context of Inverse Theory—the collection of techniques used in geophysics...
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Statistical assessment of interbasin water transfer for karst areas (Turkey)
The intensification of drought and unsustainable management of water resources has caused increasing demand for water resources. Interbasin water...
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Non-equilibrium Statistical Mechanics
In this chapter we consider macroscopic systems that are not in equilibrium. Examples are fluids and gases as described by fluid dynamics, deformable...
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Ensemble Kalman Inversion for Determining Model Parameter of Self-potential Data in the Mineral Exploration
Self-potential (SP) method has been increasingly popular in geophysical exploration of mineral resources using an assumption that the causative...
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Map** of earthquake hotspot and coldspot zones for identifying potential landslide hotspot areas in the Himalayan region
Landslide and earthquake are two of the dangerous natural hazards in the Himalayan mountainous ranges. This study focused on small-scale landslide...
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High-resolution geoid modeling using least squares modification of Stokes and Hotine formulas in Colorado
The Colorado geoid experiment was initiated and organized as a joint study by the Joint Working Group (JWG) 2.2.2 (1-cm geoid experiment) of the...
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Self-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors
The iteratively reweighted least-squares approach to self-tuning robust adjustment of parameters in linear regression models with autoregressive (AR)...
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Complex/Hilbert EOFs
Weather and Climate data contain a myriad of processes including oscillating and propagating features. In general EOF method is not suited to...
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A new method for gridding passive microwave data with mixed measurements and spatial correlation
In this article we develop a new method to grid passive microwave data in the presence of spatial correlation patterns. Our proposal combines a...
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Atmospheric deposition and precipitation are important predictors of inorganic nitrogen export to streams from forest and grassland watersheds: a large-scale data synthesis
Previous studies have evaluated how changes in atmospheric nitrogen (N) inputs and climate affect stream N concentrations and fluxes, but none have...
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Background Error Covariance Statistics of Hydrometeor Control Variables Based on Gaussian Transform
Use of data assimilation to initialize hydrometeors plays a vital role in numerical weather prediction (NWP). To directly analyze hydrometeors in...
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Forecasting reservoir-induced landslide deformation using genetic algorithm enhanced multivariate Taylor series Kalman filter
Given the uncertain nature of reservoir-induced landslides, develo** a relatively simple forecast model with high accuracy and strong robustness is...
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Model Based Four and Six Component Decompositions for Soil Moisture Retrieval
Soil moisture in bare and vegetation covered soil and its spatio-temporal variation is of great importance for various applications in the field of...
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Classification of Sailboat Tell Tail Based on Deep Learning
The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface. It is of great significance...
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A spatial copula interpolation in a random field with application in air pollution data
Interpolating a skewed conditional spatial random field with missing data is cumbersome in the absence of Gaussianity assumptions. Copulas can...
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Random Walks Partitioning and Network Reliability Assessing in Water Distribution System
A novel network partition model is presented within the water distribution system (WDS). Firstly, random walk community detection (RWCD) is employed...
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Time-Series Analysis
Time-series analysis, introduced in this chapter, is used to investigate the temporal behavior of a variable. Sections 5.2–5.6 introduces methods of...
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Computational Geoscience
A systematic approach to the evaluation of geochemical data involves the use of multivariate methods that identify processes. These processes are...