Anthropogenic Aquifer Recharge : WSP Methods in Water Resources Evaluation Series No. 5 / Robert G. Maliva |
Autore | Maliva, Robert G. |
Pubbl/distr/stampa | Cham, : Springer, 2020 |
Descrizione fisica | XXV, 861 p. : ill. ; 24 cm |
Disciplina |
577.6(Inquinamento acqua - Ecologia acquatica)
550(Scienze della terra e geologia - Geofisica) 338.927(Tecnologia alternativa. Economia ambientale. Sviluppo sostenibile) 551(Geologia, idrogeologia, meteorologia) 628(Ingegneria ambientale. Sostenibilità dell'ambiente) |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNICAMPANIA-VAN0237364 |
Maliva, Robert G. | ||
Cham, : Springer, 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
|
APAC 2019 : Proceedings of the 10th International Conference on Asian and Pacific Coasts, 2019, Hanoi, Vietnam / editors Nguyen Trung Viet, Dou Xiping, Tran Thanh Tung |
Pubbl/distr/stampa | Singapore, : Springer, 2020 |
Descrizione fisica | XXII, 1483 p. : ill. ; 24 cm |
Disciplina |
550(Scienze della terra e geologia - Geofisica)
526.982(Fotogrammetria) 551.46(Oceanografia e geologia sottomarina) |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNICAMPANIA-VAN0238163 |
Singapore, : Springer, 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Vanvitelli | ||
|
Apennines : Tectonics, Sedimentation, and Magmatism from the Palaeozoic to the Present / / edited by Domenico Liotta, Giancarlo Molli, Angelo Cipriani |
Pubbl/distr/stampa | Basel : , : MDPI, , 2023 |
Descrizione fisica | 1 online resource (454 pages) |
Disciplina | 550 |
Soggetto topico | Earth sciences |
ISBN | 3-0365-2252-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Altri titoli varianti | Apennines |
Record Nr. | UNINA-9910683372403321 |
Basel : , : MDPI, , 2023 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Application of Satellite Gravimetry to Mass Transports on a Global Scale and the Tibetan Plateau [[electronic resource] /] / by Shuang Yi |
Autore | Yi Shuang |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XV, 143 p.) |
Disciplina |
550
526.1 |
Collana | Springer Theses, Recognizing Outstanding Ph.D. Research |
Soggetto topico |
Geophysics
Hydrogeology Oceanography Climate change Geophysics/Geodesy Climate Change |
ISBN | 981-13-7353-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Introduction -- Data -- Mass inversion method of GRACE data -- Global sea level change -- Terrestrial water storage change in Asia -- Glacial and tectonic mass change in High Mountain Asia -- Conclusion. |
Record Nr. | UNINA-9910350333803321 |
Yi Shuang | ||
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Application of Soft Computing and Intelligent Methods in Geophysics [[electronic resource] /] / by Alireza Hajian, Peter Styles |
Autore | Hajian Alireza |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (XVII, 533 p. 410 illus., 247 illus. in color.) |
Disciplina |
550
526.1 |
Collana | Springer Geophysics |
Soggetto topico |
Geophysics
Geotechnical engineering Mathematical physics Computer science—Mathematics Artificial intelligence Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Mathematical Applications in the Physical Sciences Math Applications in Computer Science Artificial Intelligence |
ISBN | 3-319-66532-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Neural networks :concepts /applications in: Seismic,EM,Gravity,VLF,conductivity,GPR -- Fuzzy logic:concepts /applications in: Seismic,EM,Gravity,VLF,conductivity,GPR -- Neuro-fuzzy concepts /applications in: Seismic,EM,Gravity,VLF,conductivity,GPR -- Genetic Algorithm: concepts /applications in: Seismic,EM,Gravity,VLF,conductivity,GPR -- Future of soft computing methods in geophysics. . |
Record Nr. | UNINA-9910299379603321 |
Hajian Alireza | ||
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Applications & investigations in earth science / Edward J. Tarbuck, Frederick K. Lutgens, Kenneth G. Pinzke ; illustrations by Dennis Tasa |
Autore | TARBUCK, Edward J. |
Edizione | [3. ed.] |
Pubbl/distr/stampa | Upper Saddle River : Prentice Hall, 2000 |
Descrizione fisica | VIII, 353 p. : ill. ; 28 cm |
Disciplina | 550 |
Altri autori (Persone) |
LUTGENS, Frederick K.
PINZKE, Kenneth G. |
Soggetto topico | Scienze della terra |
ISBN | 0-13-011288-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996301146803316 |
TARBUCK, Edward J. | ||
Upper Saddle River : Prentice Hall, 2000 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Applications of linear and nonlinear models : fixed effects, random effects, and total least squares / / Joseph L. Awange, Erik W. Grafarend, Silvelyn Zwanzig |
Autore | Awange Joseph L. <1969-> |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (1127 pages) |
Disciplina | 550 |
Collana | Springer geophysics |
Soggetto topico |
Geophysics
Linear models (Statistics) Mathematical models Geofísica Models lineals (Estadística) Models matemàtics |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-94598-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Foreword -- Contents -- Preface to the First Edition -- Preface to the Second Edition -- Chapter 1 The First Problem of Algebraic Regression -- 1-1 Introduction -- 1-11 The Front Page Example -- 1-12 The Front Page Example: Matrix Algebra -- 1-13 The Front Page Example: MINOS, Horizontal Rank Partitioning -- 1-14 The Range R(f) and the Kernel N(f) -- 1-15 The Interpretation of MINOS -- 1-2 Minimum Norm Solution (MINOS) -- 1-21 A Discussion of the Metric of the Parameter Space X -- 1-22 An Alternative Choice of the Metric of the Parameter Space X -- 1-23 Gx-MINOS and Its Generalized Inverse -- 1-24 Eigenvalue Decomposition of Gx-MINOS: Canonical MINOS -- 1-3 Case Study -- 1-31 Fourier Series -- 1-32 Fourier-Legendre Series -- 1-33 Nyquist Frequency for Spherical Data -- 1-4 Special Nonlinear Models -- 1-41 Taylor Polynomials, Generalized Newton Iteration -- 1-42 Linearized Models with Datum Defect -- 1-5 Notes -- Chapter 2 The First Problem of Probabilistic Regression: The Bias Problem -- 2-1 Linear Uniformly Minimum Bias Estimator (LUMBE) -- 2-2 The Equivalence Theorem of Gx-MINOS and S-LUMBE -- 2-3 Example -- Chapter 3 The Second Problem of Algebraic Regression -- 3-1 Introduction -- 3-11 The Front Page Example -- 3-12 The Front Page Example in Matrix Algebra -- 3-13 Least Squares Solution of the Front Page Example by Means of Vertical Rank Partitioning -- 3-14 The RangeR(f) and the Kernel N(f), Interpretation of "LESS" by Three Partitionings -- 3-2 The Least Squares Solution: "LESS" -- 3-21 A Discussion of the Metric of the Parameter Space X -- 3-22 Alternative Choices of the Metric of the Observation Y -- 3-23 Gx-LESS and Its Generalized Inverse -- 3-24 Eigenvalue Decomposition of Gy-LESS: Canonical LESS -- 3-3 Case Study -- 3-31 Canonical Analysis of the Hat Matrix, Partial Redundancies, High Leverage Points.
3-32 Multilinear Algebra, "Join" and "Meet", the Hodge Star Operator -- 3-33 From A to B: Latent Restrictions, Grassmann Coordinates, Plücker Coordinates -- 3-34 From B to A: Latent Parametric Equations, Dual Grassmann Coordinates, Dual Plücker Coordinates -- 3-35 Break Points -- 3-4 Special Linear and Nonlinear Models: A Family of Means for Direct Observations -- 3-5 A Historical Note on C.F. Gauss and A.M. Legendre -- Chapter 4 The Second Problem of Probabilistic Regression -- 4-1 Introduction -- 4-11 The Front Page Example -- 4-12 Estimators of Type BLUUE and BIQUUE of the Front Page Example -- 4-13 BLUUE and BIQUUE of the Front Page Example, Sample Median, Median Absolute Deviation -- 4-14 Alternative Estimation Maximum Likelihood (MALE) -- 4-2 Setup of the Best Linear Uniformly Unbiased Estimator -- 4-21 The Best Linear Uniformly Unbiased Estimation ^ξ of ξ : Σy-BLUUE -- 4-22 The Equivalence Theorem of Gy-LESS and Σy-BLUUE -- 4-3 Setup of the Best Invariant Quadratic Uniformly Unbiased Estimator -- 4-31 Block Partitioning of the Dispersion Matrix and Linear Space Generated by Variance-Covariance Components -- 4-32 Invariant Quadratic Estimation of Variance-Covariance Components of Type IQE -- 4-33 Invariant Quadratic Uniformly Unbiased Estimations of Variance-Covariance Components of Type IQUUE -- 4-34 Invariant Quadratic Uniformly Unbiased Estimationsof One Variance Component (IQUUE) from Σy-BLUUE: HIQUUE -- 4-35 Invariant Quadratic Uniformly Unbiased Estimators of Variance Covariance Components of Helmert Type: HIQUUE Versus HIQE -- 4-36 Best Quadratic Uniformly Unbiased Estimations of One Variance Component: BIQUUE -- 4-37 Simultaneous Determination of First Moment and the Second Central Moment, Inhomogeneous Multilinear Estimation, the E - D Correspondence, Bayes Designwith Moment Estimations. Chapter 5 The Third Problem of Algebraic Regression -- 5-1 Introduction -- 5-11 The Front Page Example -- 5-12 The Front Page Example in Matrix Algebra -- 5-13 Minimum Norm: Least Squares Solution of the Front Page Example by Means of Additive Rank Partitioning -- 5-14 Minimum Norm: Least Squares Solution of the Front Page Example by Means of Multiplicative Rank Partitioning -- 5-15 The Range R(f) and the Kernel N(f) Interpretation of "MINOLESS" by Three Partitionings -- 5-2 MINOLESS and Related Solutions Like Weighted Minimum Norm-Weighted Least Squares Solutions -- 5-21 The Minimum Norm-Least Squares Solution: "MINOLESS" -- 5-22 (Gx, Gy)-MINOS and Its Generalized Inverse -- 5-23 Eigenvalue Decomposition of (Gx, Gy)-MINOLESS -- 5-24 Notes -- 5-3 The Hybrid Approximation Solution: α-HAPS and Tykhonov-Phillips Regularization -- Chapter 6 The Third Problem of Probabilistic Regression -- 6-1 Setup of the Best Linear Minimum Bias Estimator of Type BLUMBE -- 6-11 Definitions, Lemmas and Theorems -- 6-12 The First Example: BLUMBE Versus BLE, BIQUUE Versus BIQE, Triangular Leveling Network -- 6-2 Setup of the Best Linear Estimators of Type hom BLE, hom S-BLE and hom a-BLE for Fixed Effects -- 6-3 Continuous Networks -- 6-31 Continuous Networks of Second Derivatives Type -- Chapter 7 Overdetermined System of Nonlinear Equations on Curved Manifolds -- 7-1 Introduction -- 7-2 Minimal Geodesic Distance: MINGEODISC -- 7-3 Special Models: From the Circular Normal Distribution to the Oblique Normal Distribution -- 7-31 A Historical Note of the von Mises Distribution -- 7-32 Oblique Map Projection -- 7-33 A Note on the Angular Metric -- 7-4 Case Study -- References -- Chapter 8 The Fourth Problem of Probabilistic Regression -- 8-1 The Random Effect Model -- 8-2 Examples. Chapter 9 The Fifth Problem of Algebraic Regression: The System of Conditional Equations: Homogeneous and Inhomogeneous Equations: {By = Bi versus -c + By = Bi} -- 9-1 Gy-LESS of a System of a Inconsistent Homogeneous Conditional Equations -- 9-2 Solving a System of Inconsistent Inhomogeneous Conditional Equations -- 9-3 Examples -- Chapter 10 The Fifth Problem of Probabilistic Regression -- 10-1 Inhomogeneous General Linear Gauss-Markov Model (Fixed Effects and Random Effects) -- 10-2 Explicit Representations of Errors in the General Gauss-Markov Model with Mixed Effects -- 10-3 An Example for Collocation -- 10-4 Comments -- Chapter 11 The sixth problem of probabilistic regression -- 11-1 Introduction -- 11-2 The Errors-in-Variables Model and its Symmetry -- 11-3 Least Squares in Linear Errors-in-Variables Models -- 11-31 Naive Least Squares -- 11-32 Total Least Squares TLS -- 11-4 SIMEX and SYMEX -- 11-41 SIMEX -- 11-42 SYMEX -- 11-5 Datum Transformation -- 11-6 Nonlinear Errors-in-Variables Models -- Chapter 12 The Nonlinear Problem of the 3d Datum Transformation and the Procrustes Algorithm -- 12-1 The 3d Datum Transformation and the Procrustes Algorithm -- 12-2 The Variance: Covariance Matrix of the Error Matrix E -- 12-3 References -- Chapter 13 The Sixth Problem of Generalized Algebraic Regression -- 13-1 Variance-Covariance-Component Estimation in the Linear Model Ax + ε = y, y ∉ R(A) -- 13-2 Variance-Covariance-Component Estimation in the Linear Model Bε = By -c, By ∉ R(A) + c -- 13-3 Variance-Covariance-Component Estimation in theLinear Model Ax + ε + Bε = By -c, By ∉ R(A) + c -- 13-4 The Block Structure of Dispersion Matrix D{y} -- Chapter 14 Special Problems of Algebraic Regression and Stochastic Estimation -- 14-1 The Multivariate Gauss-Markov Model: A Special Problem of Probabilistic Regression -- 14-2 n-Way Classification Models. 14-21 A First Example: 1-Way Classification -- 14-22 A Second Example: 2-Way Classification Without Interaction -- 14-23 A Third Example: 2-Way Classification with Interaction -- 14-24 Higher Classifications with Interaction -- 14-3 Dynamical Systems -- Chapter 15 Systems of equations: Hybrid algebraic-numeric solutions -- 15-1 Algebraic, numeric, and hybrid algebraic-numeric -- 15-2 Algebraic solutions: Background -- 15-3 Nonlinear systems of equations: Algebraic methods -- 15-31 Nonlinear Gauss-Markov model: Algebraic solution -- 15-32 Adjustment of the combinatorial subsets -- 15-4 Examples -- 15-5 Hybrid algebraic-numeric methods -- 15-6 Notes -- Chapter 16 Integer Least Squares -- 16-1 Introductory remarks -- 16-2 Model for Positioning -- 16-3 Mixed Integer Linear Model -- 16-4 Integer Least Squares -- 16-41 Simple Rounding Solution -- 16-42 Main Steps -- 16-43 The Closest Vector Problem (CVP) -- 16-44 Reduction -- 16-45 Gram-Schmidt Method -- 16-46 The LLL Algorithm -- 16-47 Babai's Rounding Technique -- Chapter 17 Bayesian Inference -- 17-1 Introduction -- 17-2 Principle of Bayesian Analysis -- 17-21 Sequential Analysis -- 17-22 Hierarchical Bayes Models -- 17-23 Choice of Prior -- 17-24 Bayesian Inference -- 17-3 Univariate Linear Model -- 17-31 Model Assumptions -- 17-32 Normal-inverse-gamma Distribution -- 17-33 Noninformative Prior -- 17-34 Conjugate Prior -- 17-35 Regularized Estimators -- 17-4 Mixed Model -- 17-41 Prior Distribution -- 17-42 Posterior Distribution -- 17-5 Multivariate Linear Model -- 17-51 Normal-inverse-Wishart Distribution -- 17-52 Noninformative Prior -- 17-53 Informative Prior -- 17-6 Computer Intensive Methods -- 17-61 Independent Monte Carlo (MC) -- 17-62 Importance Sampling -- 17-63 Markov Chain Monte Carlo -- 17-64 Gibbs Sampling -- 17-65 Rejection Algorithm -- 17-66 Approximative Bayesian Computation (ABC). Appendix A Tensor Algebra, Linear Algebra, Matrix Algebra, Multilinear Algebra. |
Record Nr. | UNISA-996495171203316 |
Awange Joseph L. <1969-> | ||
Cham, Switzerland : , : Springer, , [2022] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Applications of linear and nonlinear models : fixed effects, random effects, and total least squares / / Joseph L. Awange, Erik W. Grafarend, Silvelyn Zwanzig |
Autore | Awange Joseph L. <1969-> |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (1127 pages) |
Disciplina | 550 |
Collana | Springer geophysics |
Soggetto topico |
Geophysics
Linear models (Statistics) Mathematical models Geofísica Models lineals (Estadística) Models matemàtics |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-94598-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Foreword -- Contents -- Preface to the First Edition -- Preface to the Second Edition -- Chapter 1 The First Problem of Algebraic Regression -- 1-1 Introduction -- 1-11 The Front Page Example -- 1-12 The Front Page Example: Matrix Algebra -- 1-13 The Front Page Example: MINOS, Horizontal Rank Partitioning -- 1-14 The Range R(f) and the Kernel N(f) -- 1-15 The Interpretation of MINOS -- 1-2 Minimum Norm Solution (MINOS) -- 1-21 A Discussion of the Metric of the Parameter Space X -- 1-22 An Alternative Choice of the Metric of the Parameter Space X -- 1-23 Gx-MINOS and Its Generalized Inverse -- 1-24 Eigenvalue Decomposition of Gx-MINOS: Canonical MINOS -- 1-3 Case Study -- 1-31 Fourier Series -- 1-32 Fourier-Legendre Series -- 1-33 Nyquist Frequency for Spherical Data -- 1-4 Special Nonlinear Models -- 1-41 Taylor Polynomials, Generalized Newton Iteration -- 1-42 Linearized Models with Datum Defect -- 1-5 Notes -- Chapter 2 The First Problem of Probabilistic Regression: The Bias Problem -- 2-1 Linear Uniformly Minimum Bias Estimator (LUMBE) -- 2-2 The Equivalence Theorem of Gx-MINOS and S-LUMBE -- 2-3 Example -- Chapter 3 The Second Problem of Algebraic Regression -- 3-1 Introduction -- 3-11 The Front Page Example -- 3-12 The Front Page Example in Matrix Algebra -- 3-13 Least Squares Solution of the Front Page Example by Means of Vertical Rank Partitioning -- 3-14 The RangeR(f) and the Kernel N(f), Interpretation of "LESS" by Three Partitionings -- 3-2 The Least Squares Solution: "LESS" -- 3-21 A Discussion of the Metric of the Parameter Space X -- 3-22 Alternative Choices of the Metric of the Observation Y -- 3-23 Gx-LESS and Its Generalized Inverse -- 3-24 Eigenvalue Decomposition of Gy-LESS: Canonical LESS -- 3-3 Case Study -- 3-31 Canonical Analysis of the Hat Matrix, Partial Redundancies, High Leverage Points.
3-32 Multilinear Algebra, "Join" and "Meet", the Hodge Star Operator -- 3-33 From A to B: Latent Restrictions, Grassmann Coordinates, Plücker Coordinates -- 3-34 From B to A: Latent Parametric Equations, Dual Grassmann Coordinates, Dual Plücker Coordinates -- 3-35 Break Points -- 3-4 Special Linear and Nonlinear Models: A Family of Means for Direct Observations -- 3-5 A Historical Note on C.F. Gauss and A.M. Legendre -- Chapter 4 The Second Problem of Probabilistic Regression -- 4-1 Introduction -- 4-11 The Front Page Example -- 4-12 Estimators of Type BLUUE and BIQUUE of the Front Page Example -- 4-13 BLUUE and BIQUUE of the Front Page Example, Sample Median, Median Absolute Deviation -- 4-14 Alternative Estimation Maximum Likelihood (MALE) -- 4-2 Setup of the Best Linear Uniformly Unbiased Estimator -- 4-21 The Best Linear Uniformly Unbiased Estimation ^ξ of ξ : Σy-BLUUE -- 4-22 The Equivalence Theorem of Gy-LESS and Σy-BLUUE -- 4-3 Setup of the Best Invariant Quadratic Uniformly Unbiased Estimator -- 4-31 Block Partitioning of the Dispersion Matrix and Linear Space Generated by Variance-Covariance Components -- 4-32 Invariant Quadratic Estimation of Variance-Covariance Components of Type IQE -- 4-33 Invariant Quadratic Uniformly Unbiased Estimations of Variance-Covariance Components of Type IQUUE -- 4-34 Invariant Quadratic Uniformly Unbiased Estimationsof One Variance Component (IQUUE) from Σy-BLUUE: HIQUUE -- 4-35 Invariant Quadratic Uniformly Unbiased Estimators of Variance Covariance Components of Helmert Type: HIQUUE Versus HIQE -- 4-36 Best Quadratic Uniformly Unbiased Estimations of One Variance Component: BIQUUE -- 4-37 Simultaneous Determination of First Moment and the Second Central Moment, Inhomogeneous Multilinear Estimation, the E - D Correspondence, Bayes Designwith Moment Estimations. Chapter 5 The Third Problem of Algebraic Regression -- 5-1 Introduction -- 5-11 The Front Page Example -- 5-12 The Front Page Example in Matrix Algebra -- 5-13 Minimum Norm: Least Squares Solution of the Front Page Example by Means of Additive Rank Partitioning -- 5-14 Minimum Norm: Least Squares Solution of the Front Page Example by Means of Multiplicative Rank Partitioning -- 5-15 The Range R(f) and the Kernel N(f) Interpretation of "MINOLESS" by Three Partitionings -- 5-2 MINOLESS and Related Solutions Like Weighted Minimum Norm-Weighted Least Squares Solutions -- 5-21 The Minimum Norm-Least Squares Solution: "MINOLESS" -- 5-22 (Gx, Gy)-MINOS and Its Generalized Inverse -- 5-23 Eigenvalue Decomposition of (Gx, Gy)-MINOLESS -- 5-24 Notes -- 5-3 The Hybrid Approximation Solution: α-HAPS and Tykhonov-Phillips Regularization -- Chapter 6 The Third Problem of Probabilistic Regression -- 6-1 Setup of the Best Linear Minimum Bias Estimator of Type BLUMBE -- 6-11 Definitions, Lemmas and Theorems -- 6-12 The First Example: BLUMBE Versus BLE, BIQUUE Versus BIQE, Triangular Leveling Network -- 6-2 Setup of the Best Linear Estimators of Type hom BLE, hom S-BLE and hom a-BLE for Fixed Effects -- 6-3 Continuous Networks -- 6-31 Continuous Networks of Second Derivatives Type -- Chapter 7 Overdetermined System of Nonlinear Equations on Curved Manifolds -- 7-1 Introduction -- 7-2 Minimal Geodesic Distance: MINGEODISC -- 7-3 Special Models: From the Circular Normal Distribution to the Oblique Normal Distribution -- 7-31 A Historical Note of the von Mises Distribution -- 7-32 Oblique Map Projection -- 7-33 A Note on the Angular Metric -- 7-4 Case Study -- References -- Chapter 8 The Fourth Problem of Probabilistic Regression -- 8-1 The Random Effect Model -- 8-2 Examples. Chapter 9 The Fifth Problem of Algebraic Regression: The System of Conditional Equations: Homogeneous and Inhomogeneous Equations: {By = Bi versus -c + By = Bi} -- 9-1 Gy-LESS of a System of a Inconsistent Homogeneous Conditional Equations -- 9-2 Solving a System of Inconsistent Inhomogeneous Conditional Equations -- 9-3 Examples -- Chapter 10 The Fifth Problem of Probabilistic Regression -- 10-1 Inhomogeneous General Linear Gauss-Markov Model (Fixed Effects and Random Effects) -- 10-2 Explicit Representations of Errors in the General Gauss-Markov Model with Mixed Effects -- 10-3 An Example for Collocation -- 10-4 Comments -- Chapter 11 The sixth problem of probabilistic regression -- 11-1 Introduction -- 11-2 The Errors-in-Variables Model and its Symmetry -- 11-3 Least Squares in Linear Errors-in-Variables Models -- 11-31 Naive Least Squares -- 11-32 Total Least Squares TLS -- 11-4 SIMEX and SYMEX -- 11-41 SIMEX -- 11-42 SYMEX -- 11-5 Datum Transformation -- 11-6 Nonlinear Errors-in-Variables Models -- Chapter 12 The Nonlinear Problem of the 3d Datum Transformation and the Procrustes Algorithm -- 12-1 The 3d Datum Transformation and the Procrustes Algorithm -- 12-2 The Variance: Covariance Matrix of the Error Matrix E -- 12-3 References -- Chapter 13 The Sixth Problem of Generalized Algebraic Regression -- 13-1 Variance-Covariance-Component Estimation in the Linear Model Ax + ε = y, y ∉ R(A) -- 13-2 Variance-Covariance-Component Estimation in the Linear Model Bε = By -c, By ∉ R(A) + c -- 13-3 Variance-Covariance-Component Estimation in theLinear Model Ax + ε + Bε = By -c, By ∉ R(A) + c -- 13-4 The Block Structure of Dispersion Matrix D{y} -- Chapter 14 Special Problems of Algebraic Regression and Stochastic Estimation -- 14-1 The Multivariate Gauss-Markov Model: A Special Problem of Probabilistic Regression -- 14-2 n-Way Classification Models. 14-21 A First Example: 1-Way Classification -- 14-22 A Second Example: 2-Way Classification Without Interaction -- 14-23 A Third Example: 2-Way Classification with Interaction -- 14-24 Higher Classifications with Interaction -- 14-3 Dynamical Systems -- Chapter 15 Systems of equations: Hybrid algebraic-numeric solutions -- 15-1 Algebraic, numeric, and hybrid algebraic-numeric -- 15-2 Algebraic solutions: Background -- 15-3 Nonlinear systems of equations: Algebraic methods -- 15-31 Nonlinear Gauss-Markov model: Algebraic solution -- 15-32 Adjustment of the combinatorial subsets -- 15-4 Examples -- 15-5 Hybrid algebraic-numeric methods -- 15-6 Notes -- Chapter 16 Integer Least Squares -- 16-1 Introductory remarks -- 16-2 Model for Positioning -- 16-3 Mixed Integer Linear Model -- 16-4 Integer Least Squares -- 16-41 Simple Rounding Solution -- 16-42 Main Steps -- 16-43 The Closest Vector Problem (CVP) -- 16-44 Reduction -- 16-45 Gram-Schmidt Method -- 16-46 The LLL Algorithm -- 16-47 Babai's Rounding Technique -- Chapter 17 Bayesian Inference -- 17-1 Introduction -- 17-2 Principle of Bayesian Analysis -- 17-21 Sequential Analysis -- 17-22 Hierarchical Bayes Models -- 17-23 Choice of Prior -- 17-24 Bayesian Inference -- 17-3 Univariate Linear Model -- 17-31 Model Assumptions -- 17-32 Normal-inverse-gamma Distribution -- 17-33 Noninformative Prior -- 17-34 Conjugate Prior -- 17-35 Regularized Estimators -- 17-4 Mixed Model -- 17-41 Prior Distribution -- 17-42 Posterior Distribution -- 17-5 Multivariate Linear Model -- 17-51 Normal-inverse-Wishart Distribution -- 17-52 Noninformative Prior -- 17-53 Informative Prior -- 17-6 Computer Intensive Methods -- 17-61 Independent Monte Carlo (MC) -- 17-62 Importance Sampling -- 17-63 Markov Chain Monte Carlo -- 17-64 Gibbs Sampling -- 17-65 Rejection Algorithm -- 17-66 Approximative Bayesian Computation (ABC). Appendix A Tensor Algebra, Linear Algebra, Matrix Algebra, Multilinear Algebra. |
Record Nr. | UNINA-9910616381603321 |
Awange Joseph L. <1969-> | ||
Cham, Switzerland : , : Springer, , [2022] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Applied Geoinformatics for Sustainable Integrated Land and Water Resources Management (ILWRM) in the Brahmaputra River basin [[electronic resource] ] : Results from the EC-project BRAHMATWINN / / edited by Nayan Sharma, Wolfgang-Albert Flügel |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | New Delhi : , : Springer India : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (81 p.) |
Disciplina |
004
300 333.7 338.927 550 551.48 910 |
Soggetto topico |
Sustainable development
Water Geography Computer science Earth sciences Social sciences Sustainable Development Water, general Geography, general Computer Science, general Earth Sciences, general Social Sciences, general |
ISBN | 81-322-1967-8 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 1. Introduction -- 2. Conceptual Background of Applied Geoinformatics -- 3. The Ec-project Brahmatwinn -- 4. Regional Climate Projections -- 5. Land use / Land Cover Classification of the Natural Environment -- 6. Glacier Changes and Permafrost Distribution -- 7. Wetlands and their Dynamics -- 8. Large Scale Distributed Hydrological Modelling -- 9. Applying the Response Units (ru) Concept for iwrm -- 10. Vulnerability Assessment and Scenarios -- 11. Adaptive iwrm Responses to cope with “what-if?” Scenarios -- 12. Integrated Land and Water Resources Management System (ilwrms) -- 13. References. |
Record Nr. | UNINA-9910299437603321 |
New Delhi : , : Springer India : , : Imprint : Springer, , 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Applied Geology [[electronic resource] ] : Approaches to Future Resource Management / / edited by Marina De Maio, Ashwani Kumar Tiwari |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (XVII, 316 p. 138 illus., 118 illus. in color.) |
Disciplina | 550 |
Soggetto topico |
Natural disasters
Urban geography Remote sensing Earth sciences Natural Hazards Urban Geography / Urbanism (inc. megacities, cities, towns) Remote Sensing/Photogrammetry Earth Sciences, general |
ISBN | 3-030-43953-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Part I: Hydrogeology and Aquifer Contamination -- Chapter 1. Geological and hydrogeological characterization of springs in a DSGSD context (Rodoretto Valley - NW Italian Alps) (Martina Gizzi, Stefano Lo Russo, Maria Gabriella Forno, Elena Cerino Abdin, Glenda Taddia) -- Chapter 2. Evaluation and prediction of seepage discharge through tailings dams when their rising (Viacheslav V. Fetisov, Elena A. Menshikova) -- Chapter 3. Sediment yield in mountain basins, analysis and management: the SMART-SED project (Davide Brambilla, Monica Papini, Vladislav Ivov Ivanov, Luca Bonaventura, Andrea Abbate, Laura Longoni) -- Chapter 4. Natural groundwater background levels of nitrate and landfill effects (Apulia, Southern Italy) (Livia Emanuela Zuffianò, Pier Paolo Limoni, Giorgio De Giorgio, Maurizio Polemio) -- Part II: Geology and Urban areas -- Chapter 5. Sinkholes in the Friuli Venezia Giulia Region focus on the evaporites (Chiara Calligaris, Luca Zini, Stefania Nisio, Chiara Piano) -- Chapter 6. Collapses in calcarenitic deposits along the sides of the Ginosa ravine in south Italy (Angelo Doglioni, Vincenzo Simeone) -- Chapter 7. Relation between on field and InSAR data on landslide-induced damage (Matteo Del Soldato, Silvia Bianchini, Pantaleone De Vita, Diego Di Martire, Roberto Tomás, Domenico Calcaterra, Nicola Casagli) -- Chapter 8. A hierarchical model for the Rocca di Sciara north-eastern slope instabilities (Sicily, Italy) (Mario Valiante, Francesca Bozzano, Marta Della Seta, Domenico Guida) -- Part III: Geomechanics -- Chapter 9. Comparing direct and indirect methods to estimate Uniaxial Compressive Strength of rocks belonging to the Dolomites sequence (NE Italian Alps) (Elia Longo, Ennio Chiesurin, Mario Floris) -- Chapter 10. CO2 sequestration and enhanced coalbed methane recovery: Worldwide status and Indian scenario (Bankim Mahanta, Vikram Vishal) -- Part IV: Landslide: Monitoring -- Chapter 11. Hydrological behavior of unsaturated shallow soils on a slope and its failure mechanism: a case study in Ren River catchment, China (Xinsheng Wei, Wen Fan, Massimiliano Bordoni, Claudia Meisina) -- Chapter 12. First steps for the development of an optical fibre strain sensor for shallow landslide stability monitoring through laboratory experiments (Monica Papini, Vladislav Ivov Ivanov, Davide Brambilla, Maddalena Ferrario, Marco Brunero, Gabriele Cazzulani, Laura Longoni) -- Chapter 13. The giant Seymareh Landslide (Zagros Mts., Iran): a lesson for evaluating multi-temporal hazard scenarios (Michele Delchiaro, Javad Rouhi, Marta Della Seta, Salvatore Martino, Reza Nozaem, Maryam Dehbozorgi) -- Chapter 14. Towards real-time geodetic monitoring of landslides with GNSS mass-market devices (Paolo Dabove, Ambrogio M. Manzino, Alberto Cina, Marco Piras, Iosif H. Bendea) -- Part V: Landslide: Climate change -- Chapter 15. Italian latest advances on rainfall thresholds for landslide triggering (Stefano Luigi Gariano, Samuele Segoni, Luca Piciullo) -- Chapter 16. Validation of a shallow landslide susceptibility analysis through a real case study: an example of application in Rome (Italy) (Poueme Djueyep Geraud, Esposito Carlo, Schilirò Luca, Bozzano Francesca) -- Part VI: Landslide: Control -- Chapter 17. Application of a generalized criterion: time-of-failure forecast and alert thresholds assessment for landslides (Alessandro Valletta, Andrea Segalini, Andrea Carri) -- Chapter 18. Evaluation of prediction capability of the MaxEnt and Frequency Ratio methods for landslide susceptibility in the Vernazza catchment (Cinque Terre, Italy) (Emanuele Raso, Diego Di Martire, Andrea Cevasco, Domenico Calcaterra, Patrizio Scarpellini, Marco Firpo). |
Record Nr. | UNINA-9910411921703321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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