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Selective Maintenance Modelling and Optimization [[electronic resource] ] : Basic Methods and Some Recent Advances / / by Yu Liu, Hong-Zhong Huang, Tao Jiang
Selective Maintenance Modelling and Optimization [[electronic resource] ] : Basic Methods and Some Recent Advances / / by Yu Liu, Hong-Zhong Huang, Tao Jiang
Autore Liu Yu
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (197 pages)
Disciplina 620.00452
Collana Springer Series in Reliability Engineering
Soggetto topico Industrial design
Mathematical optimization
Stochastic models
Industrial Design
Optimization
Stochastic Modelling
ISBN 3-031-17323-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. Introduction -- Chapter 2. Basic Selective Maintenance Model -- Chapter 3. Selective Maintenance for Multi-State Systems Under Imperfect Maintenance -- Chapter 4. Selective Maintenance for Multi-State Systems with Loading Strategy -- Chapter 5. Selective Maintenance under Stochastic Time Durations of Breaks and Maintenance Actions -- Chapter 6. Robust Selective Maintenance under Imperfect Observations -- Chapter 7. Selective Maintenance and Inspection Optimization for Partially Observable Systems -- Chapter 8. Selective Maintenance for Systems Operating Multiple Consecutive Missions -- Chapter 9. Dynamic Selective Maintenance for Multi-State Systems Operating Multiple Consecutive Missions. .
Record Nr. UNINA-9910645890203321
Liu Yu  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Seven Fundamental Concepts in Spacetime Physics / / Vesselin Petkov
Seven Fundamental Concepts in Spacetime Physics / / Vesselin Petkov
Autore Petkov Vesselin <1949->
Edizione [Second edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2024]
Descrizione fisica 1 online resource (115 pages)
Disciplina 570.113
Collana SpringerBriefs in Physics Series
Soggetto topico Biology - Mathematical models
Pattern formation (Biology)
Stochastic models
ISBN 3-031-49730-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Spacetime -- Inertial and Accelerated Motion in Spacetime Physics -- Origin and Nature of Inertia in Spacetime Physics -- Relativistic Mass -- Gravitation -- Gravitational Waves -- Black Holes.
Record Nr. UNINA-9910800111703321
Petkov Vesselin <1949->  
Cham, Switzerland : , : Springer, , [2024]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Simulating copulas : stochastic models, sampling algorithms, and applications / Jan-Frederik Mai, Matthias Scherer
Simulating copulas : stochastic models, sampling algorithms, and applications / Jan-Frederik Mai, Matthias Scherer
Autore Mai, Jan-Frederik
Pubbl/distr/stampa London : Imperial College Press
Descrizione fisica xiv, 295 p. : ill. ; 24 cm
Disciplina 519.535
Altri autori (Persone) Scherer, Matthiasauthor
Collana Series in quantitative finance, 1756-1604 ; 4
Soggetto topico Copulas (Mathematical statistics)
Stochastic models
ISBN 9781848168749
1848168748
Classificazione AMS 62-06
LC QA273.6.M35
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991002016999707536
Mai, Jan-Frederik  
London : Imperial College Press
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Spatial Fleming-Viot models with selection and mutation / Donald A. Dawson, Andreas Greven
Spatial Fleming-Viot models with selection and mutation / Donald A. Dawson, Andreas Greven
Autore Dawson, Donald Andrew
Descrizione fisica xvii, 856 p. : ill. ; 24 cm
Disciplina 519.2
Altri autori (Persone) Greven, Andreasauthor
Collana Lecture notes in mathematics, 0075-8434 ; 2092
Soggetto topico Population genetics - Mathematical models
Punctuated equilibrium (Evolution) - Mathematical models
Stochastic models
Markov processes
ISBN 9783319021522 (pbk.)
3319021524 (pbk.)
Classificazione AMS 60J70
AMS 92D15
AMS 92D25
AMS 60J80
AMS 60J85
LC QA3.L28
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991003324699707536
Dawson, Donald Andrew  
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Stability problems for stochastic models : proceedings of the 9th international seminar held in Varna, Bulgaria, May 13-19, 1985 / / Vladimir Kalashnikov, Boyan Penkov, Vladimir Zolotarev
Stability problems for stochastic models : proceedings of the 9th international seminar held in Varna, Bulgaria, May 13-19, 1985 / / Vladimir Kalashnikov, Boyan Penkov, Vladimir Zolotarev
Autore Kalashnikov Vladimir
Edizione [1st ed. 1987.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer-Verlag, , [1987]
Descrizione fisica 1 online resource (VIII, 224 p.)
Disciplina 003.76
Collana Lecture Notes in Mathematics
Soggetto topico Stochastic models
ISBN 3-540-47394-7
Classificazione 60-06
62-06
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto The estimation of the rate of convergence in the integral limit theorem in the Euclidean motion group -- Contribution to the analytic theory of linear forms of independent random variables -- ?p-strictly stable laws and estimation of their parameters -- The method of metric distances in the problem of estimation of the deviation from the exponential distribution -- The accuracy of the normal approximation to the distribution of the sum of a random number of independent random variables -- Mixtures of probability distributions -- Some limit theorems for summability methods of I.I.D.Random variables -- Properties of mode of spectral positive stable distributions -- Two characterizations using records -- On orthogonal-series estimators for probability distributions -- Estimates of the deviation between the exponential and new classes of bivariate distributions -- On the difference between distributions of sums and maxima -- On the inequalities of Berry-Esseen and V.M. Zolotarev -- Some fixed point theorems probabilistic metric spaces -- The asymptotic bias in a deviation of a location model -- Cramer's decomposition theorem within the continuation of distribution functions -- An asymptotically most Bias-Robust invariant estimator of location -- Characterizing the distributions of the random vectors X 1, X 2, X 3 by the distribution of the statistic (X 1–X 3, X 2–X 3) -- On stability estimates of Cramer's theorem -- On the estimation of moments of regenerative cycles in a general closed central-server queueing network -- On F-processes and their applications -- On some properties of ideal metrics of order ? -- On ?-independence of sample mean and sample variance.
Record Nr. UNISA-996466379003316
Kalashnikov Vladimir  
Berlin, Heidelberg : , : Springer-Verlag, , [1987]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications [[electronic resource] ] : Selected Contributions from SimStat 2019 and Invited Papers / / edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke
Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications [[electronic resource] ] : Selected Contributions from SimStat 2019 and Invited Papers / / edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke
Autore Pilz Jürgen
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (265 pages)
Disciplina 519.57
Altri autori (Persone) MelasViatcheslav B
BathkeArne
Collana Contributions to Statistics
Soggetto topico Statistics
Mathematical statistics - Data processing
Experimental design
Machine learning
Stochastic models
Statistical Theory and Methods
Statistics and Computing
Design of Experiments
Machine Learning
Applied Statistics
Stochastic Modelling in Statistics
ISBN 3-031-40055-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- Part I Invited Papers -- 1 Likelihood Ratios in Forensics: What They Are and What They Are Not -- 1.1 Introduction -- 1.2 Lindley's Likelihood Ratio (LLR) -- 1.2.1 Notations -- 1.2.2 A Frequentist Framework for Lindley's Likelihood Ratio (LLR) -- 1.3 Score-Based Likelihood Ratio (SLR) -- 1.3.1 The Expression of the SLR -- 1.3.2 The Glass Example -- 1.4 Discussion -- References -- 2 MANOVA for Large Number of Treatments -- 2.1 Introduction -- 2.2 Notations and Model Setup -- 2.3 Simulations -- 2.3.1 MANOVA Tests for Large g -- 2.3.2 Special Case: ANOVA for Large g -- 2.4 Discussion and Outlook -- References -- 3 Pollutant Dispersion Simulation by Means of a Stochastic Particle Model and a Dynamic Gaussian Plume Model -- 3.1 Introduction -- 3.2 Meteorological Monitoring Network -- 3.3 Wind Field Modeling -- 3.3.1 Mass Correction of the Wind Field -- 3.3.2 Plume Rise -- 3.4 Stochastic Particle Model -- 3.4.1 Deposition -- 3.4.2 Implementation -- 3.5 Dynamic Gaussian Plume Model -- 3.6 Implementation on the Server -- 3.7 A Real-World Example with Application to an Alpine Valley -- 3.8 Conclusions and Outlook -- References -- 4 On an Alternative Trigonometric Strategy for StatisticalModeling -- 4.1 Introduction -- 4.2 The Alternative Sine Distribution -- 4.2.1 Presentation -- 4.2.2 Moment Properties -- 4.2.3 Parametric Extensions -- 4.3 AS Generated Family -- 4.3.1 Definition -- 4.3.2 Series Expansions -- 4.3.3 Example: The ASE Exponential Distribution -- 4.3.4 Moment Properties -- 4.4 Application to a Famous Cancer Data -- 4.5 Conclusion -- References -- Part II Design of Experiments -- 5 Incremental Construction of Nested Designs Basedon Two-Level Fractional Factorial Designs -- 5.1 Introduction -- 5.2 Greedy Coffee-House Design -- 5.3 Two-Level Fractional Factorial Designs -- 5.3.1 Half Fractions: m=1.
5.3.2 Several Generators -- 5.3.2.1 Defining Relations -- 5.3.2.2 Resolution -- 5.3.2.3 Word Length Pattern -- 5.3.3 Minimum Size -- 5.4 Two-Level Factorial Designs and Error-Correcting Codes -- 5.4.1 Definitions and Properties -- 5.4.2 Examples -- 5.5 Maximin Distance Properties of Two-Level Factorial Designs -- 5.5.1 Neighbouring Pattern and Distant Site Pattern -- 5.5.2 Optimal Selection of Generators by Simulated Annealing -- 5.5.2.1 SA Algorithm for the Maximisation of ρH -- 5.6 Covering Properties of Two-Level Factorial Designs -- 5.6.1 Bounds on CRH(Xn) -- 5.6.2 Calculation of CRH(Xn) -- 5.6.2.1 Algorithmic Construction of a Lower Bound on CRH(Xn) -- 5.7 Greedy Constructions Based on Fractional Factorial Designs -- 5.7.1 Base Designs -- 5.7.2 Rescaled Designs -- 5.7.3 Projection Properties -- 5.8 Summary and Future Work -- Appendix -- References -- 6 A Study of L-Optimal Designs for the Two-Dimensional Exponential Model -- 6.1 Introduction -- 6.2 Equivalence Theorem for L-Optimal Designs -- 6.3 General Case -- 6.4 Excess and Saturated Designs -- References -- 7 Testing for Randomized Block Single-Case Designsby Combined Permutation Tests with Multivariate Mixed Data -- 7.1 Introduction -- 7.2 Randomized Block Single-Case Designs and NPC -- 7.3 Simulation Study -- 7.4 A Real Case Study -- 7.5 Conclusions -- References -- 8 Adaptive Design Criteria Motivated by a Plug-In Percentile Estimator -- 8.1 Introduction -- 8.2 Problem Formulation and Background -- 8.2.1 Problem Formulation -- 8.2.2 Background -- 8.3 The Plug-In Estimator -- 8.4 Adaptive ``Plug-In'' Criteria -- 8.4.1 Monte Carlo Approximation -- 8.4.2 Monte Carlo Approximation Assuming Independency -- 8.4.3 Assuming Independency and Neglecting Uncertainty -- 8.4.4 Using SUR Design Criterion for Exceedance Probability -- 8.5 Numerical Implementation -- 8.6 Numerical Study.
8.6.1 Comparison Study -- 8.6.2 Methodology -- 8.6.2.1 Case Studies -- 8.6.2.2 Performance Indicators -- 8.6.3 Numerical Results -- 8.6.3.1 Estimators Performance -- 8.6.3.2 Implementation -- 8.6.3.3 Criteria -- 8.7 Conclusions -- Appendix 1 -- Posterior Mean and Variance of f Under the Gaussian Process Assumption -- SUR Design Criteria for Exceedance Probability Estimation -- Appendix 2 -- References -- Part III Queueing and Inventory Analysis -- 9 On a Parametric Estimation for a Convolutionof Exponential Densities -- 9.1 Introduction -- 9.2 Convolution of the Exponential Densities -- 9.3 ML Estimation of the Parameters -- 9.4 Parameter's Estimation by the Moments' Method -- 9.5 Approximation of the Density -- 9.6 Experimental Study -- 9.7 Application to a Single Queueing System M/G/1/k -- 9.8 Conclusions -- References -- 10 Statistical Estimation with a Known Quantileand Its Application in a Modified ABC-XYZ Analysis -- 10.1 Introduction -- 10.2 Methods -- 10.2.1 Statistical Estimation with a Known Quantile -- 10.2.2 ABC-XYZ Analysis -- 10.3 ABC-XYZ Analysis Modified with a Known Quantile -- 10.4 Conclusions -- References -- Part IV Machine Learning and Applications -- 11 A Study of Design of Experiments and Machine Learning Methods to Improve Fault Detection Algorithms -- 11.1 Introduction -- 11.2 Design of Experiments and Machine Learning Modelling -- 11.3 Application to Fault Detection -- 11.3.1 Design of Experiments Step -- 11.3.2 Machine Learning Modelling Step -- 11.3.2.1 Refrigerant Undercharge: Fault Detection -- 11.3.2.2 Condenser Fouling: Fault Detection -- 11.4 Conclusions -- References -- 12 Microstructure Image Segmentation Using Patch-Based Clustering Approach -- 12.1 Introduction -- 12.2 Input Data -- 12.3 Previous Work -- 12.4 Grain Segmentation -- 12.4.1 Seeded Region Growing (SRG) -- 12.4.2 Image Denoising and Patch Determination.
12.4.3 Feature Extraction -- 12.4.4 Patch Clustering -- 12.4.5 Implementation -- 12.5 Results -- 12.6 Conclusion and Outlook -- References -- 13 Clustering and Symptom Analysis in Binary Datawith Application -- 13.1 Introduction -- 13.2 The Symptom Analysis -- 13.2.1 The Symptom and Syndrome Definition -- 13.2.2 Impulse Vector and Super-symptoms -- 13.2.3 Prefigurations of Super-symptom -- 13.2.4 The Super-symptom Recovery by Vector β -- 13.2.5 Clustering in Dichotomous Space and Symptom Analysis -- 13.3 The Medical Application of the Clustering and Symptom Analysis in Binary Data -- 13.3.1 Dataset -- 13.3.2 Result and Discussion -- 13.4 Conclusion -- References -- 14 Big Data for Credit Risk Analysis: Efficient Machine Learning Models Using PySpark -- 14.1 Introduction -- 14.2 Data Processing -- 14.2.1 Data Treatment -- 14.2.2 Data Storage and Distribution -- 14.2.3 Munge Data -- 14.2.4 Creating New Measures -- 14.2.5 Missing Values Imputation and Outliers Treatment -- 14.2.6 One-Hot Code and Dummy Variables -- 14.2.7 Final Dataset -- 14.3 Method and Models -- 14.3.1 Method -- 14.3.2 Model Building -- 14.4 Results and Credit Scorecard Conversion -- 14.5 Conclusion -- Appendix 1 -- Appendix 2 -- References.
Record Nr. UNINA-9910754092903321
Pilz Jürgen  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Stochastic benchmarking : theory and applications / / Alireza Amirteimoori, [and four others]
Stochastic benchmarking : theory and applications / / Alireza Amirteimoori, [and four others]
Autore Amirteimoori Alireza
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (154 pages)
Disciplina 658.562
Collana International Series in Operations Research and Management Science
Soggetto topico Stochastic models
ISBN 3-030-89869-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910523800003321
Amirteimoori Alireza  
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Stochastic Dynamic Response and Stability of Ships and Offshore Platforms [[electronic resource] /] / by Yingguang Wang
Stochastic Dynamic Response and Stability of Ships and Offshore Platforms [[electronic resource] /] / by Yingguang Wang
Autore Wang Yingguang
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (368 pages)
Disciplina 799
Collana Ocean Engineering & Oceanography
Soggetto topico Mechanics, Applied
Mechanical engineering
Stochastic models
Engineering Mechanics
Mechanical Engineering
Stochastic Modelling in Statistics
ISBN 981-9958-53-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1 Introduction -- Chapter 2 State of the art -- Chapter 3 The Monte Carlo simulation method -- Chapter 4 The numerical path integral solution method -- Chapter 5 The global geometric method -- Chapter 6 The first passage theory -- Chapter 7 Concluding remarks.
Record Nr. UNINA-9910760300203321
Wang Yingguang  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Stochastic geometry for wireless networks / / Martin Haenggi, University of Notre Dame, Indiana [[electronic resource]]
Stochastic geometry for wireless networks / / Martin Haenggi, University of Notre Dame, Indiana [[electronic resource]]
Autore Haenggi Martin
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2013
Descrizione fisica 1 online resource (xv, 284 pages) : digital, PDF file(s)
Disciplina 621.39/80151922
Soggetto topico Wireless communication systems - Mathematics
Stochastic models
ISBN 1-316-08953-3
1-139-79385-3
1-139-77948-6
1-139-78346-7
1-139-78247-9
1-139-77644-4
1-139-04381-1
1-283-71462-0
1-139-77796-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Part I. Point Process Theory: 1. Introduction; 2. Description of point processes; 3. Point process models; 4. Sums and products over point processes; 5. Interference and outage in wireless networks; 6. Moment measures of point processes; 7. Marked point processes; 8. Conditioning and Palm theory; Part II. Percolation, Connectivity and Coverage: 9. Introduction; 10. Bond and site percolation; 11. Random geometric graphs and continuum percolation; 12. Connectivity; 13. Coverage; Appendix: introduction to R.
Record Nr. UNINA-9910452958303321
Haenggi Martin  
Cambridge : , : Cambridge University Press, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Stochastic geometry for wireless networks / / Martin Haenggi, University of Notre Dame, Indiana [[electronic resource]]
Stochastic geometry for wireless networks / / Martin Haenggi, University of Notre Dame, Indiana [[electronic resource]]
Autore Haenggi Martin
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2013
Descrizione fisica 1 online resource (xv, 284 pages) : digital, PDF file(s)
Disciplina 621.39/80151922
Soggetto topico Wireless communication systems - Mathematics
Stochastic models
ISBN 1-316-08953-3
1-139-79385-3
1-139-77948-6
1-139-78346-7
1-139-78247-9
1-139-77644-4
1-139-04381-1
1-283-71462-0
1-139-77796-3
Classificazione TEC061000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Part I. Point Process Theory: 1. Introduction; 2. Description of point processes; 3. Point process models; 4. Sums and products over point processes; 5. Interference and outage in wireless networks; 6. Moment measures of point processes; 7. Marked point processes; 8. Conditioning and Palm theory; Part II. Percolation, Connectivity and Coverage: 9. Introduction; 10. Bond and site percolation; 11. Random geometric graphs and continuum percolation; 12. Connectivity; 13. Coverage; Appendix: introduction to R.
Record Nr. UNINA-9910779342903321
Haenggi Martin  
Cambridge : , : Cambridge University Press, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui