ALBERT

Description / Table of Contents: Front Cover -- Machine Learning Techniques for Space Weather -- Copyright -- Contents -- Contributors -- Introduction -- Machine Learning and Space Weather -- Scope and Structure of the Book -- Acknowledgments -- References -- Part I: Space Weather -- Chapter 1: Societal and Economic Importance of Space Weather -- 1 What is Space Weather? -- 2 Why Now? -- 3 Impacts -- 3.1 Geomagnetically Induced Currents -- 3.2 Global Navigation Satellite Systems -- 3.3 Single-Event Effects -- 3.4 Other Radio Systems -- 3.5 Satellite Drag -- 4 Looking to the Future -- 5 Summary and Conclusions -- Acknowledgments -- References -- Chapter 2: Data Availability and Forecast Products for Space Weather -- 1 Introduction -- 2 Data and Models Based on Machine Learning Approaches -- 3 Space Weather Agencies -- 3.1 Government Agencies -- 3.1.1 NOAA's Data and Products -- 3.1.2 NASA -- 3.1.3 European Space Agency -- 3.1.4 The US Air Force Weather Wing -- 3.2 Academic Institutions -- 3.2.1 Kyoto University, Japan -- 3.2.2 Rice University, USA -- 3.2.3 Laboratory for Atmospheric and Space Physics, USA -- 3.3 Commercial Providers -- 3.4 Other Nonprofit, Corporate Research Agencies -- 3.4.1 USGS -- 3.4.2 JHU Applied Physics Lab -- 3.4.3 US Naval Research Lab -- 3.4.4 Other International Service Providers -- 4 Summary -- References -- Part II: Machine Learning -- Chapter 3: An Information-Theoretical Approach to Space Weather -- 1 Introduction -- 2 Complex Systems Framework -- 3 State Variables -- 4 Dependency, Correlations, and Information -- 4.1 Mutual Information as a Measure of Nonlinear Dependence -- 4.2 Cumulant-Based Cost as a Measure of Nonlinear Dependence -- 4.3 Causal Dependence -- 4.4 Transfer Entropy and Redundancy as Measures of Causal Relations -- 4.5 Conditional Redundancy -- 4.6 Significance of Discriminating Statistics

Description / Table of Contents: 4.7 Mutual Information and Information Flow -- 5 Examples From Magnetospheric Dynamics -- 6 Significance as an Indicator of Changes in Underlying Dynamics -- 6.1 Detecting Dynamics in a Noisy System -- 6.2 Cumulant-Based Information Flow -- 7 Discussion -- 8 Summary -- Acknowledgments -- References -- Chapter 4: Regression -- 1 What is Regression? -- 2 Learning From Noisy Data -- 2.1 Prediction Errors -- 2.2 A Probabilistic Set-Up -- 2.3 The Least Squares Method for Linear Regression -- 2.3.1 The Least Squares Method and the Best Linear Predictor -- 2.3.2 The Least Squares Method and the Maximum Likelihood Principle -- 2.3.3 A More General Approach and Higher-Order Predictors -- 2.4 Overfitting -- 2.4.1 The Order Selection Problem -- Error Decomposition: The Bias Versus Variance Trade-Off -- Some Popular Order Selection Criteria -- 2.4.2 Regularization -- 2.5 From Point Predictors to Interval Predictors -- 2.5.1 Distribution-Free Interval Predictors -- 2.6 Probability Density Estimation -- 3 Predictions Without Probabilities -- 3.1 Approximation Theory -- Dense Sets -- Best Approximator -- 3.1.1 Neural Networks -- The Backpropagation Algorithm: High-Level Idea -- Multiple Layers Networks (Deep Networks) -- 4 Probabilities Everywhere: Bayesian Regression -- 4.1 Gaussian Process Regression -- 5 Learning in the Presence of Time: Identification of Dynamical Systems -- 5.1 Linear Time-Invariant Systems -- 5.2 Nonlinear Systems -- References -- Chapter 5: Supervised Classification: Quite a Brief Overview -- 1 Introduction -- 1.1 Learning, Not Modeling -- 1.2 An Outline -- 2 Classifiers -- 2.1 Preliminaries -- 2.2 The Bayes Classifier -- 2.3 Generative Probabilistic Classifiers -- 2.4 Discriminative Probabilistic Classifiers -- 2.5 Losses and Hypothesis Spaces -- 2.5.1 0-1 Loss -- 2.5.2 Convex Surrogate Losses

Description / Table of Contents: 2.5.3 Particular Surrogate Losses -- 2.6 Neural Networks -- 2.7 Neighbors, Trees, Ensembles, and All that -- 2.7.1 k Nearest Neighbors -- 2.7.2 Decision Trees -- 2.7.3 Multiple Classifier Systems -- 3 Representations and Classifier Complexity -- 3.1 Feature Transformations -- 3.1.1 The Kernel Trick -- 3.2 Dissimilarity Representation -- 3.3 Feature Curves and the Curse of Dimensionality -- 3.4 Feature Extraction and Selection -- 4 Evaluation -- 4.1 Apparent Error and Holdout Set -- 4.2 Resampling Techniques -- 4.2.1 Leave-One-Out and k-Fold Cross-Validation -- 4.2.2 Bootstrap Estimators -- 4.2.3 Tests of Significance -- 4.3 Learning Curves and the Single Best Classifier -- 4.4 Some Words About More Realistic Scenarios -- 5 Regularization -- 6 Variations on Standard Classification -- 6.1 Multiple Instance Learning -- 6.2 One-Class Classification, Outliers, and Reject Options -- 6.3 Contextual Classification -- 6.4 Missing Data and Semisupervised Learning -- 6.5 Transfer Learning and Domain Adaptation -- 6.6 Active Learning -- Acknowledgments -- References -- Part III: Applications -- Chapter 6: Untangling the Solar Wind Drivers of the Radiation Belt: An Information Theoretical Approach -- 1 Introduction -- 2 Data Set -- 3 Mutual Information, Conditional Mutual Information, and Transfer Entropy -- 4 Applying Information Theory to Radiation Belt MeV Electron Data -- 4.1 Radiation Belt MeV Electron Flux Versus Vsw -- 4.2 Radiation Belt MeV Electron Flux Versus nsw -- 4.3 Anticorrelation of Vsw and nsw and Its Effect on Radiation Belt -- 4.4 Ranking of Solar Wind Parameters Based on Information Transfer to Radiation Belt Electrons -- 4.5 Detecting Changes in the System Dynamics -- 5 Discussion -- 5.1 Geo-Effectiveness of Solar Wind Velocity -- 5.2 nsw and Vsw Anticorrelation

Description / Table of Contents: 5.3 Geo-Effectiveness of Solar Wind Density -- 5.4 Revisiting the Triangle Distribution -- 5.5 Improving Models With Information Theory -- 5.5.1 Selecting Input Parameters -- 5.5.2 Detecting Nonstationarity in System Dynamics -- 5.5.3 Prediction Horizon -- 6 Summary -- Acknowledgments -- References -- Chapter 7: Emergence of Dynamical Complexity in the Earth's Magnetosphere -- 1 Introduction -- 2 On Complexity and Dynamical Complexity -- 3 Coherence and Intermittent Features in Time Series Geomagnetic Indices -- 4 Scale-Invariance and Self-Similarity in Geomagnetic Indices -- 5 Near-Criticality Dynamics -- 6 Multifractional Features and Dynamical Phase Transitions -- 7 Summary -- Acknowledgments -- References -- Chapter 8: Applications of NARMAX in Space Weather -- 1 Introduction -- 2 NARMAX Methodology -- 2.1 Forward Regression Orthogonal Least Square -- 2.2 The Noise Model -- 2.3 Model Validation -- 2.4 Summary -- 3 NARMAX and Space Weather Forecasting -- 3.1 Geomagnetic Indices -- 3.1.1 SISO Dst Index -- 3.1.2 Continuous Time Dst model -- 3.1.3 MISO Dst -- 3.1.4 Kp Index -- 3.2 Radiation Belt Electron Fluxes -- 3.2.1 GOES High Energy -- 3.2.2 SNB3GEO Comparison With NOAA REFM -- 3.2.3 GOES Low Energy -- 3.3 Summary of NARMAX Models -- 4 NARMAX and Insight Into the Physics -- 4.1 NARMAX Deduced Solar Wind-Magnetosphere Coupling Function -- 4.2 Identification of Radiation Belt Control Parameters -- 4.2.1 Solar Wind Density Relationship With Relativistic Electrons at GEO -- 4.2.2 Geostationary Local Quasilinear Diffusion vs. Radial Diffusion -- 4.3 Frequency Domain Analysis of the Dst Index -- 5 Discussions and Conclusion -- References -- Chapter 9: Probabilistic Forecasting of Geomagnetic Indices Using Gaussian Process Models -- 1 Geomagnetic Time Series and Forecasting -- 2 Dst Forecasting

Description / Table of Contents: 2.1 Models and Algorithms -- 2.2 Probabilistic Forecasting -- 3 Gaussian Processes -- 3.1 Gaussian Process Regression: Formulation -- 3.2 Gaussian Process Regression: Inference -- 4 One-Hour Ahead Dst Prediction -- 4.1 Data Source: OMNI -- 4.2 Gaussian Process Dst Model -- 4.3 Gaussian Process Auto-Regressive (GP-AR) -- 4.4 GP-AR With eXogenous Inputs (GP-ARX) -- 5 One-Hour Ahead Dst Prediction: Model Design -- 5.1 Choice of Mean Function -- 5.2 Choice of Kernel -- 5.3 Model Selection: Hyperparameters -- 5.3.1 Grid Search -- 5.3.2 Coupled Simulated Annealing -- 5.3.3 Maximum Likelihood -- 5.4 Model Selection: Auto-Regressive Order -- 6 GP-AR and GP-ARX: Workflow Summary -- 7 Practical Issues: Software -- 8 Experiments and Results -- 8.1 Model Selection and Validation Performance -- 8.2 Comparison of Hyperparameter Selection Algorithms -- 8.3 Final Evaluation -- 8.4 Sample Predictions With Error Bars -- 9 Conclusion -- References -- Chapter 10: Prediction of MeV Electron Fluxes and Forecast Verification -- 1 Relativistic Electrons in Earth's Outer Radiation Belt -- 1.1 Source, Loss, Transport, and Acceleration, Variation -- 2 Numerical Techniques in Radiation Belt Forecasting -- 3 Relativistic Electron Forecasting and Verification -- 3.1 Forecast Verification -- 3.2 Relativistic Electron Forecasting -- 4 Summary -- References -- Chapter 11: Artificial Neural Networks for Determining Magnetospheric Conditions -- 1 Introduction -- 2 A Brief Review of ANNs -- 3 Methodology and Application -- 3.1 The DEN2D Model -- 4 Advanced Applications -- 4.1 The DEN3D Model -- 4.2 The Chorus and Hiss Wave Models -- 4.3 Radiation Belt Flux Modeling -- 5 Summary and Discussion -- Acknowledgments -- References -- Chapter 12: Reconstruction of Plasma Electron Density From Satellite Measurements Via Artificial Neural Networks

Description / Table of Contents: 1 Overview

Description / Table of Contents: Abstract This Special Publication highlights the importance of clays and clayey material, and their multiple roles, in many national geological disposal facilities for higher activity radioactive wastes. Clays can be both the disposal facility host rock and part of its intrinsic engineered barriers, and may be present in the surrounding geological environment. Clays possess various characteristics that make them high-quality barriers to the migration of radionuclides and chemical contaminants, e.g. very little water movement, diffusive transport, retention capacity, self-sealing capacity, stability over millions of years, homogeneity and lateral continuity. The 20 papers presented in this Special Publication cover a range of topics related to clays in radioactive waste confinement. Aspects of clay characterization and behaviour at various temporal and spatial scales relevant to the confinement of radionuclides in clay are discussed, from phenomenological processes to the overall understanding of the performance and safety of geological disposal facilities.

Description / Table of Contents: Simon Norris: Radioactive waste confinement: clays in natural and engineered barriers – introduction / Geological Society, London, Special Publications, 443:1-8, first published on March 1, 2017, doi:10.1144/SP443.26 --- Large-scale geological characterization --- K. Vandersteen, B. Leterme, and M. Gedeon: Regional aquifer hydrogeochemistry in the confined aquifer system below the Boom Clay (NE Belgium): data analysis and modelling / Geological Society, London, Special Publications, 443:9-28, first published on June 22, 2016, doi:10.1144/SP443.7 --- Peter Gravesen, Stig A. Schack Pedersen, Bertel Nilsson, and Merete Binderup: An assessment of Palaeogene and Neogene clay deposits in Denmark as possible host rocks for final disposal of low- and intermediate-level radioactive waste / Geological Society, London, Special Publications, 443:29-38, first published on June 22, 2016, doi:10.1144/SP443.3 --- General strategy for clay-based disposal systems --- S. Doudou, E. J. Harvey, P. J. Richardson, S. M. Wickham, P. Van Marcke, D. Raymaekers, and W. Wacquier: Approaches to evaluate and underpin the technical feasibility of the Belgian disposal concept / Geological Society, London, Special Publications, 443:39-48, first published on June 24, 2016, doi:10.1144/SP443.11 --- S. Doudou, M. J. White, M. Johnson, J.-M. Bosgiraud, and Pär Grahm: DOPAS full-scale experiments: approaches to compliance assessment / Geological Society, London, Special Publications, 443:49-58, first published on August 26, 2016, doi:10.1144/SP443.16 --- Jiří Svoboda, Jaroslav Pacovský, Markéta Dvořáková, Irena Hanusová, Petr Večerník, and Dagmar Trpkošová: DOPAS EPSP experiment / Geological Society, London, Special Publications, 443:59-72, first published on August 26, 2016, doi:10.1144/SP443.17 --- Dagmar Trpkošová, Petr Večerník, Jenny Gondolli, Václava Havlová, Jiří Svoboda, and Irena Hanusová: Laboratory experiments on bentonite pellet saturation / Geological Society, London, Special Publications, 443:73-83, first published on November 3, 2016, doi:10.1144/SP443.22 --- Geomechanics --- Hua Shao, Sebastian Göthling, Wenting Liu, Jürgen Hesser, Jacques Morel, and Jürgen Sönnke: Quantitative characterization of the excavation damaged zone fracture network in the Meuse/Haute-Marne Underground Research Laboratory: in situ experiment and numerical interpretation of helium injection test / Geological Society, London, Special Publications, 443:85-96, first published on October 13, 2016, doi:10.1144/SP443.21 --- Xueqing Su, Son Nguyen, Ehsan Haghighat, Stanislaw Pietruszczak, Denis Labrie, Jean-Dominique Barnichon, and Hadj Abdi: Characterizing the mechanical behaviour of the Tournemire argillite / Geological Society, London, Special Publications, 443:97-113, first published on October 12, 2016, doi:10.1144/SP443.20 --- L.-M. Guayacán-Carrillo, J. Sulem, D. M. Seyedi, S. Ghabezloo, A. Noiret, and G. Armand: Convergence analysis of an unsupported micro-tunnel at the Meuse/Haute-Marne Underground Research Laboratory / Geological Society, London, Special Publications, 443:115-125, first published on December 20, 2016, doi:10.1144/SP443.24 --- Andrés Alcolea, Uli Kuhlmann, Paul Marschall, Andrea Lisjak, Giovanni Grasselli, Omid Mahabadi, Rémi de La Vaissière, Helen Leung, and Hua Shao: A pragmatic approach to abstract the excavation damaged zone around tunnels of a geological radioactive waste repository: application to the HG-A experiment in Mont Terri / Geological Society, London, Special Publications, 443:127-147, first published on June 24, 2016, doi:10.1144/SP443.8 --- Hua Shao, Benjamin Paul, Xuerui Wang, Jürgen Hesser, Jens Becker, Benoit Garitte, and Herwig Müller: The influence of different supports on the properties of the excavation damaged zone along the FE tunnel in the Mont Terri Underground Rock Laboratory / Geological Society, London, Special Publications, 443:149-157, first published on September 26, 2016, doi:10.1144/SP443.18 --- Mass transfer --- S. M'Jahad, C. A. Davy, F. Skoczylas, and J. Talandier: Characterization of transport and water retention properties of damaged Callovo-Oxfordian claystone / Geological Society, London, Special Publications, 443:159-177, first published on December 22, 2016, doi:10.1144/SP443.23 --- P. Jean-Baptiste, B. Lavielle, E. Fourre, T. Smith, and M. Pagel: Vertical distribution of helium and 40Ar/36Ar in porewaters of the Eastern Paris Basin (Bure/Haute-Marne): constraints on transport processes through the sedimentary sequence / Geological Society, London, Special Publications, 443:179-192, first published on December 21, 2016, doi:10.1144/SP443.25 --- Kateřina Kolomá and Radek Červinka: Study of 85Sr transport through a column filled with crushed granite in the presence of bentonite colloids / Geological Society, London, Special Publications, 443:193-203, first published on July 8, 2016, doi:10.1144/SP443.14 --- M. Aertsens, L. Van Laer, N. Maes, and J. Govaerts: An improved model for through-diffusion experiments: application to strontium and tritiated water (HTO) diffusion in Boom Clay and compacted illite / Geological Society, London, Special Publications, 443:205-210, first published on June 24, 2016, doi:10.1144/SP443.9 --- Shuo Meng and Wilfried Pfingsten: Multispecies random walk simulations in radial symmetry: model concept, benchmark, and application to HTO, 22Na and 36Cl diffusion in clay / Geological Society, London, Special Publications, 443:211-224, first published on August 18, 2016, doi:10.1144/SP443.15 --- Philipp Schaedle, Thomas Kaempfer, Guillaume Pépin, Jacques Wendling, and Juergen Brommundt: Combining high-resolution two-phase with simplified single-phase simulations in order to optimize the performance of PA/SA simulations for a deep geological repository for radioactive waste / Geological Society, London, Special Publications, 443:225-234, first published on June 22, 2016, doi:10.1144/SP443.4 --- Erdem Toprak, Sebastia Olivella, and Xavier Pintado: Coupled THM modelling of engineered barriers for the final disposal of spent nuclear fuel isolation / Geological Society, London, Special Publications, 443:235-251, first published on September 26, 2016, doi:10.1144/SP443.19 --- Olivier Bildstein, Jean-Éric Lartigue, Michel L. Schlegel, Christian Bataillon, Benoît Cochepin, Isabelle Munier, and Nicolas Michau: Gaining insight into corrosion processes from numerical simulations of an integrated iron-claystone experiment / Geological Society, London, Special Publications, 443:253-267, first published on June 22, 2016, doi:10.1144/SP443.2 --- Bentonite evolution --- Klaus-Peter Kröhn: Bentonite re-saturation: different conceptual models – similar mathematical descriptions / Geological Society, London, Special Publications, 443:269-279, first published on July 6, 2016, doi:10.1144/SP443.12 --- F. Dolder, U. Mäder, A. Jenni, and B. Münch: Alteration of MX-80 bentonite backfill material by high-pH cementitious fluids under lithostatic conditions – an experimental approach using core infiltration techniques / Geological Society, London, Special Publications, 443:281-305, first published on June 24, 2016, doi:10.1144/SP443.10 --- Heini M. Reijonen and Nuria Marcos: Chemical erosion of the bentonite buffer: do we observe it in nature? / Geological Society, London, Special Publications, 443:307-317, first published on June 24, 2016, doi:10.1144/SP443.13 --- Gas transfer --- Luc-Vincent Bénet, Étienne Blaud, and Jacques Wendling: Modelling of water and gas flow through an excavation damaged zone in the Callovo-Oxfordian argillites in the framework of a single porosity model / Geological Society, London, Special Publications, 443:319-332, first published on June 24, 2016, doi:10.1144/SP443.6 --- Jan Smutek, Lucie Hausmannova, and Jiri Svoboda: The gas permeability, breakthrough behaviour and re-sealing ability of Czech Ca–Mg bentonite / Geological Society, London, Special Publications, 443:333-348, first published on June 22, 2016, doi:10.1144/SP443.5 --- E. Jacops, N. Maes, C. Bruggeman, and A. Grade: Measuring diffusion coefficients of dissolved He and Ar in three potential clay host formations: Boom Clay, Callovo-Oxfordian Clay and Opalinus Clay / Geological Society, London, Special Publications, 443:349-360, first published on June 22, 2016, doi:10.1144/SP443.1