Active particles . Volume 3 : advances in theory, models, and applications / / Nicola Bellomo, José Antonio Carrillo, and Eitan Tadmor, editors |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2022] |
Descrizione fisica | 1 online resource (230 pages) |
Disciplina | 519.3 |
Collana | Modeling and Simulation in Science, Engineering and Technology |
Soggetto topico |
Mathematical optimization
Mathematical optimization - Computer programs Models matemàtics Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-93302-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- Variability and Heterogeneity in Natural Swarms: Experiments and Modeling -- 1 Introduction -- 2 Sources of Variability in Nature -- 2.1 Development as a Source of Variation -- 2.2 Transient Changes in the Behavior of Individuals -- 2.3 Environmentally Induced Variations -- 2.4 Social Structure -- 2.5 Inherent/Intrinsic Properties and Animal Personality -- 2.6 Variability in Microorganisms -- 3 Experiments with Heterogeneous Swarms -- 3.1 Fish -- 3.2 Mammals -- 3.3 Insects -- 3.4 Microorganisms -- 4 Modeling Heterogeneous Collective Motion -- 4.1 Continuous Models -- 4.2 Agent-Based Models -- 4.3 Specific Examples: Locust -- 4.4 Specific Examples: Microorganisms and Cells -- 5 Summary and Concluding Remarks -- References -- Active Crowds -- 1 Introduction -- 2 Models for Active Particles -- 2.1 Continuous Random Walks -- 2.1.1 Excluded-Volume Interactions -- 2.2 Discrete Random Walks -- 2.3 Hybrid Random Walks -- 3 Models for Externally Activated Particles -- 3.1 Continuous Models -- 3.2 Discrete Models -- 4 General Model Structure -- 4.1 Wasserstein Gradient Flows -- 4.2 Entropy Dissipation -- 5 Boundary Effects -- 5.1 Mass Conserving Boundary Conditions -- 5.2 Flux Boundary Conditions -- 5.3 Other Boundary Conditions -- 6 Active Crowds in the Life and Social Science -- 6.1 Pedestrian Dynamics -- 6.2 Transport in Biological Systems -- 7 Numerical Simulations -- 7.1 One Spatial Dimension -- 7.2 Two Spatial Dimensions -- References -- Mathematical Modeling of Cell Collective Motion Triggered by Self-Generated Gradients -- 1 Introduction -- 2 The Keller-Segel Model and Variations -- 2.1 The Construction of Waves by Keller and Segel -- 2.2 Positivity and Stability Issues -- 2.3 Variations on the Keller-Segel Model -- 2.4 Beyond the Keller-Segel Model: Two Scenarios for SGG.
3 Scenario 1: Strongest Advection at the Back -- 4 Scenario 2: Cell Leakage Compensated by Growth -- 5 Conclusion and Perspectives -- References -- Clustering Dynamics on Graphs: From Spectral Clustering to Mean Shift Through Fokker-Planck Interpolation -- 1 Introduction -- 1.1 Mean Shift-Based Methods -- 1.1.1 Lifting the Dynamics to the Wasserstein Space -- 1.2 Spectral Methods -- 1.2.1 Normalized Versions of the Graph Laplacian -- 1.2.2 More General Spectral Embeddings -- 1.3 Outline -- 2 Mean Shift and Fokker-Planck Dynamics on Graphs -- 2.1 Dynamic Interpretation of Spectral Embeddings -- 2.2 The Mean Shift Algorithm on Graphs -- 2.2.1 Mean Shift on Graphs as Inspired by Wasserstein Gradient Flows -- 2.2.2 Quickshift and KNF -- 3 Fokker-Planck Equations on Graphs -- 3.1 Fokker-Planck Equations on Graphs via Interpolation -- 3.2 Fokker-Planck Equation on Graphs via Reweighing and Connections to Graph Mean Shift -- 4 Continuum Limits of Fokker-Planck Equations on Graphs and Implications -- 4.1 Continuum Limit of Mean Shift Dynamics on Graphs -- 4.2 Continuum Limits of Fokker-Planck Equations on Graphs -- 4.3 The Witten Laplacian and Some Implications for Data Clustering -- 5 Numerical Examples -- 5.1 Numerical Method -- 5.2 Simulations -- 5.2.1 Graph Dynamics as Density Dynamics -- 5.2.2 Comparison of Graph Dynamics and PDE Dynamics -- 5.2.3 Clustering Dynamics -- 5.2.4 Effect of the Kernel Density Estimate on Clustering -- 5.2.5 Effect of Data Distribution on Clustering -- 5.2.6 Blue Sky Problem -- 5.2.7 Density vs. Geometry -- References -- Random Batch Methods for Classical and Quantum Interacting Particle Systems and Statistical Samplings -- 1 Introduction -- 2 The Random Batch Methods -- 2.1 The RBM Algorithms -- 2.2 Convergence Analysis -- 2.3 An Illustrating Example: Wealth Evolution -- 3 The Mean-Field Limit -- 4 Molecular Dynamics. 4.1 RBM with Kernel Splitting -- 4.2 Random Batch Ewald: An Importance Sampling in the Fourier Space -- 5 Statistical Sampling -- 5.1 Random Batch Monte Carlo for Many-Body Systems -- 5.2 RBM-SVGD: A Stochastic Version of Stein Variational Gradient Descent -- 6 Agent-Based Models for Collective Dynamics -- 6.1 The Cucker-Smale Model -- 6.2 Consensus Models -- 7 Quantum Dynamics -- 7.1 A Theoretical Result on the N-Body Schrödinger Equation -- 7.1.1 Mathematical Setting and Main Result -- 7.2 Quantum Monte Carlo Methods -- 7.2.1 The Random Batch Method for VMC -- 7.2.2 The Random Batch Method for DMC -- References -- Trends in Consensus-Based Optimization -- 1 Introduction -- 1.1 Notation and Assumptions -- 1.1.1 The Weighted Average -- 2 Consensus-Based Global Optimization Methods -- 2.1 Original Statement of the Method -- 2.1.1 Particle Scheme -- 2.1.2 Mean-Field Limit -- 2.1.3 Analytical Results for the Original Scheme Without Heaviside Function -- 2.1.4 Numerical Methods -- 2.2 Variant 1: Component-Wise Diffusion and Random Batches -- 2.2.1 Component-Wise Geometric Brownian Motion -- 2.2.2 Random Batch Method -- 2.2.3 Implementation and Numerical Results -- 2.3 Variant 2: Component-Wise Common Diffusion -- 2.3.1 Analytical Results -- 2.3.2 Numerical Results -- 3 Relationship of CBO and Particle Swarm Optimization -- 3.1 Variant 4: Personal Best Information -- 3.1.1 Performance -- 4 CBO with State Constraints -- 4.1 Variant 5: Dynamics Constrained to Hyper-Surfaces -- 4.1.1 Analytical Results -- 5 Overview of Applications -- 5.1 Global Optimization Problems: Comparison to Heuristic Methods -- 5.2 Machine Learning -- 5.3 Global Optimization with Constrained State Space -- 5.4 PDE Versus SDE Simulations -- 6 Conclusion, Outlook and Open problems -- References. |
Record Nr. | UNISA-996466417303316 |
Cham, Switzerland : , : Springer International Publishing, , [2022] | ||
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Lo trovi qui: Univ. di Salerno | ||
|
Active particles . Volume 3 : advances in theory, models, and applications / / Nicola Bellomo, José Antonio Carrillo, and Eitan Tadmor, editors |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2022] |
Descrizione fisica | 1 online resource (230 pages) |
Disciplina | 519.3 |
Collana | Modeling and Simulation in Science, Engineering and Technology |
Soggetto topico |
Mathematical optimization
Mathematical optimization - Computer programs Models matemàtics Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-93302-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- Variability and Heterogeneity in Natural Swarms: Experiments and Modeling -- 1 Introduction -- 2 Sources of Variability in Nature -- 2.1 Development as a Source of Variation -- 2.2 Transient Changes in the Behavior of Individuals -- 2.3 Environmentally Induced Variations -- 2.4 Social Structure -- 2.5 Inherent/Intrinsic Properties and Animal Personality -- 2.6 Variability in Microorganisms -- 3 Experiments with Heterogeneous Swarms -- 3.1 Fish -- 3.2 Mammals -- 3.3 Insects -- 3.4 Microorganisms -- 4 Modeling Heterogeneous Collective Motion -- 4.1 Continuous Models -- 4.2 Agent-Based Models -- 4.3 Specific Examples: Locust -- 4.4 Specific Examples: Microorganisms and Cells -- 5 Summary and Concluding Remarks -- References -- Active Crowds -- 1 Introduction -- 2 Models for Active Particles -- 2.1 Continuous Random Walks -- 2.1.1 Excluded-Volume Interactions -- 2.2 Discrete Random Walks -- 2.3 Hybrid Random Walks -- 3 Models for Externally Activated Particles -- 3.1 Continuous Models -- 3.2 Discrete Models -- 4 General Model Structure -- 4.1 Wasserstein Gradient Flows -- 4.2 Entropy Dissipation -- 5 Boundary Effects -- 5.1 Mass Conserving Boundary Conditions -- 5.2 Flux Boundary Conditions -- 5.3 Other Boundary Conditions -- 6 Active Crowds in the Life and Social Science -- 6.1 Pedestrian Dynamics -- 6.2 Transport in Biological Systems -- 7 Numerical Simulations -- 7.1 One Spatial Dimension -- 7.2 Two Spatial Dimensions -- References -- Mathematical Modeling of Cell Collective Motion Triggered by Self-Generated Gradients -- 1 Introduction -- 2 The Keller-Segel Model and Variations -- 2.1 The Construction of Waves by Keller and Segel -- 2.2 Positivity and Stability Issues -- 2.3 Variations on the Keller-Segel Model -- 2.4 Beyond the Keller-Segel Model: Two Scenarios for SGG.
3 Scenario 1: Strongest Advection at the Back -- 4 Scenario 2: Cell Leakage Compensated by Growth -- 5 Conclusion and Perspectives -- References -- Clustering Dynamics on Graphs: From Spectral Clustering to Mean Shift Through Fokker-Planck Interpolation -- 1 Introduction -- 1.1 Mean Shift-Based Methods -- 1.1.1 Lifting the Dynamics to the Wasserstein Space -- 1.2 Spectral Methods -- 1.2.1 Normalized Versions of the Graph Laplacian -- 1.2.2 More General Spectral Embeddings -- 1.3 Outline -- 2 Mean Shift and Fokker-Planck Dynamics on Graphs -- 2.1 Dynamic Interpretation of Spectral Embeddings -- 2.2 The Mean Shift Algorithm on Graphs -- 2.2.1 Mean Shift on Graphs as Inspired by Wasserstein Gradient Flows -- 2.2.2 Quickshift and KNF -- 3 Fokker-Planck Equations on Graphs -- 3.1 Fokker-Planck Equations on Graphs via Interpolation -- 3.2 Fokker-Planck Equation on Graphs via Reweighing and Connections to Graph Mean Shift -- 4 Continuum Limits of Fokker-Planck Equations on Graphs and Implications -- 4.1 Continuum Limit of Mean Shift Dynamics on Graphs -- 4.2 Continuum Limits of Fokker-Planck Equations on Graphs -- 4.3 The Witten Laplacian and Some Implications for Data Clustering -- 5 Numerical Examples -- 5.1 Numerical Method -- 5.2 Simulations -- 5.2.1 Graph Dynamics as Density Dynamics -- 5.2.2 Comparison of Graph Dynamics and PDE Dynamics -- 5.2.3 Clustering Dynamics -- 5.2.4 Effect of the Kernel Density Estimate on Clustering -- 5.2.5 Effect of Data Distribution on Clustering -- 5.2.6 Blue Sky Problem -- 5.2.7 Density vs. Geometry -- References -- Random Batch Methods for Classical and Quantum Interacting Particle Systems and Statistical Samplings -- 1 Introduction -- 2 The Random Batch Methods -- 2.1 The RBM Algorithms -- 2.2 Convergence Analysis -- 2.3 An Illustrating Example: Wealth Evolution -- 3 The Mean-Field Limit -- 4 Molecular Dynamics. 4.1 RBM with Kernel Splitting -- 4.2 Random Batch Ewald: An Importance Sampling in the Fourier Space -- 5 Statistical Sampling -- 5.1 Random Batch Monte Carlo for Many-Body Systems -- 5.2 RBM-SVGD: A Stochastic Version of Stein Variational Gradient Descent -- 6 Agent-Based Models for Collective Dynamics -- 6.1 The Cucker-Smale Model -- 6.2 Consensus Models -- 7 Quantum Dynamics -- 7.1 A Theoretical Result on the N-Body Schrödinger Equation -- 7.1.1 Mathematical Setting and Main Result -- 7.2 Quantum Monte Carlo Methods -- 7.2.1 The Random Batch Method for VMC -- 7.2.2 The Random Batch Method for DMC -- References -- Trends in Consensus-Based Optimization -- 1 Introduction -- 1.1 Notation and Assumptions -- 1.1.1 The Weighted Average -- 2 Consensus-Based Global Optimization Methods -- 2.1 Original Statement of the Method -- 2.1.1 Particle Scheme -- 2.1.2 Mean-Field Limit -- 2.1.3 Analytical Results for the Original Scheme Without Heaviside Function -- 2.1.4 Numerical Methods -- 2.2 Variant 1: Component-Wise Diffusion and Random Batches -- 2.2.1 Component-Wise Geometric Brownian Motion -- 2.2.2 Random Batch Method -- 2.2.3 Implementation and Numerical Results -- 2.3 Variant 2: Component-Wise Common Diffusion -- 2.3.1 Analytical Results -- 2.3.2 Numerical Results -- 3 Relationship of CBO and Particle Swarm Optimization -- 3.1 Variant 4: Personal Best Information -- 3.1.1 Performance -- 4 CBO with State Constraints -- 4.1 Variant 5: Dynamics Constrained to Hyper-Surfaces -- 4.1.1 Analytical Results -- 5 Overview of Applications -- 5.1 Global Optimization Problems: Comparison to Heuristic Methods -- 5.2 Machine Learning -- 5.3 Global Optimization with Constrained State Space -- 5.4 PDE Versus SDE Simulations -- 6 Conclusion, Outlook and Open problems -- References. |
Record Nr. | UNINA-9910556880003321 |
Cham, Switzerland : , : Springer International Publishing, , [2022] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advanced computing and systems for security . Volume 14 / / Rituparna Chaki [and four others], editors |
Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (213 pages) |
Disciplina | 005.8 |
Collana | Lecture notes in networks and systems |
Soggetto topico |
Computer security
Seguretat informàtica Models matemàtics Mineria de dades Algorismes computacionals |
Soggetto genere / forma |
Llibres electrònics
Congressos |
ISBN | 981-16-4294-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910734097103321 |
Gateway East, Singapore : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in computational methods and technologies in aeronautics and industry / / edited by Dietrich Knoerzer, Jacques Periaux, and Tero Tuovinen |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (290 pages) |
Disciplina | 551.48 |
Collana | Computational Methods in Applied Sciences |
Soggetto topico |
Aeronautics
Aeronàutica Models matemàtics Processament de dades |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-12019-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996503550903316 |
Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Advances in computational methods and technologies in aeronautics and industry / / edited by Dietrich Knoerzer, Jacques Periaux, and Tero Tuovinen |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (290 pages) |
Disciplina | 551.48 |
Collana | Computational Methods in Applied Sciences |
Soggetto topico |
Aeronautics
Aeronàutica Models matemàtics Processament de dades |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-12019-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910634036003321 |
Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in fuzzy group decision making / / Tin-Chih Toly Chen |
Autore | Chen Toly <1969-> |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (94 pages) |
Disciplina | 003.56 |
Collana | SpringerBriefs in Applied Sciences and Technology |
Soggetto topico |
Fuzzy decision making
Conjunts borrosos Decisió de grup Models matemàtics Group decision making - Mathematical models |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-86208-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910502611803321 |
Chen Toly <1969->
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Cham, Switzerland : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in fuzzy group decision making / / Tin-Chih Toly Chen |
Autore | Chen Toly <1969-> |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (94 pages) |
Disciplina | 003.56 |
Collana | SpringerBriefs in Applied Sciences and Technology |
Soggetto topico |
Fuzzy decision making
Conjunts borrosos Decisió de grup Models matemàtics Group decision making - Mathematical models |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-86208-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996466387303316 |
Chen Toly <1969->
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Cham, Switzerland : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Advances in Mathematical Modeling and Scientific Computing : International Conference on Recent Developments in Mathematics, Dubai, 2022 – Volume 2 / / edited by Firuz Kamalov, R. Sivaraj, Ho-Hon Leung |
Edizione | [1st ed. 2024.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2024 |
Descrizione fisica | 1 online resource (933 pages) |
Disciplina | 511.8 |
Collana | Trends in Mathematics |
Soggetto topico |
Mathematical models
Mathematical Modeling and Industrial Mathematics Models matemàtics Informàtica |
Soggetto genere / forma |
Congressos
Llibres electrònics |
ISBN |
9783031414206
3031414209 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | PART 1 - Differential Equations: High-Precision Algorithms For Fredholm Integral Equations (Awawdeh) -- A new decay estimate for a weakly dissipative viscoelastic suspension bridge (Al-Gharablic) -- Existence and uniqueness of Renormalized solution to non-coercive elliptic problem with measure data (Ou´edraogo) -- Fixed-Point Theorems Based Evaluation of Analytical Solution in Fractional Diffusion Equations (Malathi) -- Control and Synchronization of a Modified Chaotic Finance System with Integer and Non-Integer Orders (Moaddy) -- Dutch Book Methods for difference and differential equations (Gandolfi) -- Fourier modes in fluid flow and energy cascade (Afanasyeva) -- Approximate solutions of third order time fractional dispersive equations with singular and non singular kernel derivatives (Raghavendar) -- Choosing between vaccine efficacy and vaccine price: mathematical model for COVID19 (Al-arydah) -- Classification of Cosmological Wormhole Solutions in the Framework of General Relativity (Al-Ali) -- Use of Technology and Software in Mathematics Education (Jain) -- Modified VIM for the Solutions of Gas Dynamics (Fatima) -- PART 2 - Mechanics: Nanofluid containing motile gyrotactic microorganisms squeezed between parallel disks (Umavathi) -- Linear model for two layer porous bed suspended with nano sized particles (Umavathi) -- Effect of Variable Viscosity on Magnetohydrodynamics Mixed Convection Flow from a Vertical Flat Plate (Ajaykumar) -- Line effects in the Darcy-B´enard instability in a rotating anisotropic porous layer saturated with a fluid of variable viscosity (Suthar) -- Soret and Dufour Effects on Radiative MHD Thermosolutal Viscoplastic Nanofluid Mixed convective Flow Past a Bidirectional Stretching Sheet (Venkatadri) -- Influence of Slip Velocity on an Infinite Cylinder and Rough Flat Plate lubricated with couple stress fluid (Sreekala) -- Simulation of MHD Quadratic Natural Convection Flow of Nanofluid Inside a Square Enclosure with Thermal Radiation Effect (Venkatadri) -- Combined Effects of Magnetic Field and Heat Source on Double Diffusive Marangoni Convection in Fluid-Porous Structure (Manjunatha) -- Peristalsis and Taylor Dispersion of Solute in the Flow of Casson Fluid (Nagarani) -- An Aligned Magnetic field effect on Unsteady Heat and Mass Transfer Flow of non-Newtonian Fluid through Porous Medium (Maheshbabu) -- Effect of viscosity variation and slip velocity on the squeeze film characteristics between a cylinder and a plane plate with couple stress fluid (Salma) -- Turbulence Generators and Turbulence Structure (Selvam) -- Conjugate buoyant convection of nanoliquids in a porous saturated annulus (Arokiaraj) -- The characteristic of squeeze film due to Impact of couple stress and MHD on curved annular circular plates (Nair) -- An Exact Analytical Solution Marangoni Boundary Layer Flow with Heat and Mass Transfer (Hatami) -- Hybrid Nanofluid Flow and Thermal Transport Analysis in a Linearly Heated Cylindrical Annulus (Sankar) -- Influence of non-similar heating on nanofluid buoyant convection of nanofluid in a tilted porous parallelogrammic geometry (Sankar) -- Buoyant Convection of Nanofluid in an annular domain with linearly heating (Girish) -- Thermal and entropy management of nanoliquid in a discretely heated inclined square geometry (Kumara Swamy) -- Linear and Non-linear Analysis of Unicellular Rayleigh-B´enard Magneto Convection in a Micropolar Fluid Occupying Enclosures (Jestine) -- Study uf Rayleigh - Bénard - Marangoni Convention in a Microfliud with Corirlos Force (Baby) -- Performance of magnetic dipole contribution on ferromagnetic heat and mass transfer flow with the influence of non-linear radiative heat flux (Venkatadri) -- Thermogravitational Convective Flow inside a Cavity with a Heated Circular Cylinder: A Finite Difference Analysis via Vorticity Stream Function Approach (Venkatadri) -- An Unsteady Flow of Fluid Velocity, Temperature and Heat Emission on Mhd Free Convection Flow of Some Nanofuids (Ramesh Babu) Finite Element Analysis of Unsteady Dispersion in Casson Fluid Flow (Nagarani) -- Thermosolutal Convection in a Tilted Porous Parallelogrammic Enclosure with Discrete Heating and Salting (Sankar) -- An application of generalized Fourier and Fick’s law over a different non Newtonian fluid (Padmavathi) -- Micropolar nanofluid enfolded with viscous fluid: Three layer flow Operation Research Production inventory model for three levels of production with defective items, shortages including multi delivery policy (Karthikeyan) -- Accomplishment Expedients Of Batch Arrival Queuing Model by Fuzzy Ordering approach (Ramesh) -- Analysis of a M[x]/G/1 retrial queue with Secondary optional Service subject to Bernoulli Vacation, Server Breakdown and Customer Baulking (Indhira) -- Solving Neutrosophic Bi-objective Assignment Problem using Different Approaches (Anuradha) -- Analysis of Attainment Estimates of Loss System Queue (Seenivasan) -- Performance scrutinity of an M/G/1 Retrial Queue with Two-Phase Service and Preemptive Resume under Working Vacations and Working Breakdowns (Indhira) -- Models of Goal Programming & R Programming to Earmark Acreage (Shalini) -- Neutral- Bipolar Fuzzy Sets and its Applications (Rosline) -- Critical path in an intuitionistic triangular fuzzy number for Time Cost Trade Off in project network by the modified traditional method (Deepa) -- Operations on Alternate Quadra - Submerging Polar (AQSP) Fuzzy Graphs and its Applications (Rosline) -- Optimal Solution for Transportation Problems using Trapezoidal Fuzzy Numbers (Boobalan) -- Heterogeneous Queueing Model with Intermittently Obtainable Server with Feedback (Indhira) -- An Economic order quantity inventory model for the food supply chain with waste minimization based on a circular economy (Karthikeyan) -- Achievement Estimations of Priority Queue System in Fuzzy Environment (Seenivasan) -- Poisson jumps and state-dependent delay in a sequential approximation of stochastic neutral partial integro-differential systems (Pradeepa) -- A hybrid genetic algorithm based linear programming model to optimize feed cost for Indian Ruminants: With Stochastic Model in Comparison (Kuntal) -- PART 3 - Statistics: Outlier Detection using the Range Distribution Dania Dallah and Hana Sulieman (Dallah) -- Presenting a flexible class of INAR(p) models to analyze the COVID-19 series in Mauritius (Youssef) -- Prediction of Social Status on Depression by using Logistic Regression (Karthikeyan) -- Single Working Vacation Queue, Server Failure With Appearance of Backup Server (Seenivasan) -- Exploring ARIMA models with interacted lagged variables for forecasting (Dhandra) -- A Novel Hybrid Model for Time Series Forecasting Using Artificial Neural Networks and Autoregressive Integrated Moving Average Models (Baskaran) -- PART 4 - Graph Theory Sigma chromatic number of Mycielski transformation of graphs (Balamurugan) -- Bipartite Decomposition of Graphs using Chromatic Number (Karthika) -- Degree-Based Topological Indices and QSPR Analysis of Some Drugs Used in the Treatment of Dengue (Balamurugan) -- Orientation Number of Two Complete Bipartite Graphs with Linkages (Rajasekaran) -- Packing Chromatic Number of Windmill related Graphs (Santiago) -- Complementary triple connected total domination number of a graph (Mahadevan) -- Pebbling Number and 2-Pebbling property for the Middle Graphs of the graph obtained from fan graph by deleting f independent Edges (Dhivviyanandam) -- The De Brunn Graoh Ofsequential Repetition of Patterns in DNA Strings (Fong) -- Independent Domination Number of Cyclic and Acyclic Graphs (Balamurugan) -- Computation of Complete Partite- Zumkeller Graphs (Balamurugan) -- Characterizations of (gamma(i), gamma(DDS), gamma(DSNS)) – Trees (Yamuna) -- Mobius Cordial Labeling of Graphs (Balamurugan) -- Selfipendant and Extremal Pendant Graphs (Kottarathil) -- PART 5 - Mathematical Education : Computing the CD-number of Strong product of graphs (Mahadevan) -- Detection of TCC-Domination number for some product related graphs (Mahadevan) -- Learners’ Mental Constructions in Learning Circle Geometry (Brijlall) -- N - Separation Axioms in Topological Spaces (Alsalem) -- Investigating how the Activity, Classroom Discussion, and Exercise (ACE)Teaching Cycle influences Learners’ Problem-Solving and achievement in Circle Geometry (Brijlal) -- Exploring possible teacher and learner support structures to improve learner Mathematics performance (Brijlal) -- A study of Mathematical Epidemiology Model of Dengue Spread with fractional Properties (Jain). |
Record Nr. | UNINA-9910842283203321 |
Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2024 | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in modeling and simulation : festschrift for Pierre L'Ecuyer / / Zdravko Botev [and three others], editors |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (426 pages) |
Disciplina | 511.8 |
Soggetto topico |
Mathematical models
Simulation methods Models matemàtics Mètodes de simulació |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-10193-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Biography -- Contents -- Monte Carlo Methods for Pricing American Options -- 1 Introduction -- 2 American Option Pricing -- 3 Binomial Tree Method -- 4 Dynamic Programming Approach -- 4.1 Regression Methods -- 4.2 Malliavin Calculus -- 5 Control Variates -- 6 Numerical Experiments -- 7 Conclusion -- References -- Remarks on Lévy Process Simulation -- 1 Introduction -- 2 Lévy Processes -- 3 Main Examples -- 4 The ε-Algorithm -- 5 Using Complete Monotonicity Structure -- 6 Numerical Examples -- 7 Exact Simulation of X(h) and other Methods -- 8 Maxima, Minima and Other Path Functionals -- References -- Exact Sampling for the Maximum of Infinite Memory Gaussian Processes -- 1 Introduction -- 2 Basic Strategy -- 2.1 Milestone Events -- 2.2 Main Algorithm -- 3 Intermediate Steps in Algorithm 2 -- 4 Analysis of Algorithm 2 -- 4.1 Output Analysis -- 4.2 Complexity Analysis -- 5 Numerical Experiments -- 6 Conclusion -- References -- Truncated Multivariate Student Computations via Exponential Tilting -- 1 Introduction -- 2 Review of the Sequentially Tilted Proposal Density -- 3 Asymptotic Efficiency of the IS Estimator -- 4 Application to Constrained Linear Regression -- 5 Tobit Model Application -- 6 Application to ``Bayesian'' Splines for Non-negative Functions -- 7 The Reject-Regenerate Sampler -- 7.1 Nummelin Splitting of Transition Kernel -- 7.2 Rare-Event Robustness -- 8 Concluding Remarks -- References -- Quasi-Monte Carlo Methods in Portfolio Selection with Many Constraints -- 1 Introduction -- 2 Classical Portfolio Selection in a Nutshell -- 3 Portfolio Optimization with Many Constraints -- 4 Approximation of the Opportunity Set by Naïve Monte Carlo, and by Exponential Monte Carlo -- 5 Approximation of the Opportunity Set with Exponential QMC.
6 Approximating the Market Portfolio with MC, Exponential MC, and Exponential QMC -- 7 Approximating the Whole OS with MC, Exponential MC, and Exponential QMC -- 8 How to Calculate the Dispersion of a Sample Set in an OS? -- 9 Some Simulation Results -- 10 Conclusions, Outlook, and Further Practical Problem -- References -- Geometric-Moment Contraction of G/G/1 Waiting Times -- 1 Introduction -- 2 Main Results -- 3 Monte Carlo Results -- 3.1 M/M/1 Queue -- 3.2 M/G/1 Queues -- 4 Conclusions -- References -- Tractability of Approximation in the Weighted Korobov Space in the Worst-Case Setting -- 1 Introduction -- 2 Basic Definitions -- 2.1 Function Space Setting -- 2.2 Approximation in script upper H Subscript d comma alpha comma bold italic gammamathcalHd,α,γ -- 2.3 The Worst-Case Setting -- 2.4 Useful Relations -- 2.5 Relations to the Average-Case Setting -- 2.6 Notions of Tractability -- 3 The Results for normal upper A normal upper P normal upper P Subscript 2APP2 -- 4 The Results for normal upper A normal upper P normal upper P Subscript normal infinityAPPinfty -- 5 Overview and Formulation of Open Problems -- 5.1 Open Problems -- References -- Rare-Event Simulation via Neural Networks -- 1 Introduction -- 1.1 Background -- 2 Rare-Event Deep Learning -- 2.1 Networks and Loss Functions -- 2.2 Kernel Density Estimation -- 2.3 Training Procedure -- 2.4 Rare-Event Distribution -- 3 Experimental Results -- 3.1 Learning Normal Distributions -- 3.2 Normal Distribution Rare-Events -- 3.3 Learning Sum of Exponential Distributions -- 4 Conclusions and Further Research -- References -- Preintegration is Not Smoothing When Monotonicity Fails -- 1 Introduction -- 1.1 Related Work -- 1.2 The Problem -- 1.3 Informative Examples -- 1.4 Outline of This Paper -- 2 Smoothness Theorems in dd Dimensions -- 3 A High-Dimensional Example -- 4 Conclusion -- References. Combined Derivative Estimators -- 1 Introduction -- 2 Derivative Estimation -- 2.1 Background -- 2.2 Combined Estimators -- 2.3 Second Derivatives -- 2.4 Finite Difference Estimators and IPA -- 2.5 IPA and Randomized Score Functions -- 2.6 LRM Singularities -- 2.7 Generalized Likelihood Ratio Method -- 3 A Barrier Option Example -- 3.1 The Option Pricing Setting -- 3.2 The Barrier Option -- 3.3 A Combined IPA-LRM Estimator of Wang et al. ch10wang -- 3.4 GLR as a Combined IPA-LRM Estimator -- 4 Approaching Continuous Time: Averaging Low-Rank GLR Estimators -- 4.1 Approximating Continuous-Time Sensitivities -- 4.2 Averaging GLR Estimators -- 5 Concluding Remarks -- References -- A Central Limit Theorem For Empirical Quantiles in the Markov Chain Setting -- 1 Introduction -- 2 A Quantile Central Limit Theorem -- 3 A Uniform CLT for 1-Dependent Sequences -- 4 A Quantile Central Limit Theorem for Harris Processes -- 5 The Validity of Non-overlapping Batch-Means Estimation -- 6 Sufficient Conditions -- References -- Simulation of Markov Chains with Continuous State Space by Using Simple Stratified and Sudoku Latin Square Sampling -- 1 Introduction -- 2 Markov Chain Simulation with Stratified Sampling -- 2.1 Classical Monte Carlo -- 2.2 Simple Stratified Sampling -- 2.3 Sudoku Latin Square Sampling -- 3 Variance Bounds -- 3.1 Classical Monte Carlo -- 3.2 Simple Stratified Sampling -- 3.3 Sudoku Latin Square Sampling -- 4 Numerical Experiments -- 4.1 An Autoregressive Process -- 4.2 A European Put Option -- 4.3 Diffusion -- 5 Conclusions -- References -- Quasi-Random Sampling with Black Box or Acceptance-Rejection Inputs -- 1 Introduction -- 2 Methods for the Black Box Setting -- 2.1 Methods Based on the Empirical Quantile Function -- 2.2 Methods Based on a Generalized Pareto Approximation in the Tail -- 3 Combining AR with RQMC. 4 Application: Basket Option Pricing -- 5 Conclusion -- References -- A Generalized Transformed Density Rejection Algorithm -- 1 Introduction -- 2 Transformed Density Rejection with Inflection Points -- 3 Determine Signs of Second Derivatives -- 3.1 Initial Intervals -- 3.2 Splitting Intervals -- 4 The Algorithm -- 5 Applications -- 5.1 Generalized Hyperbolic Distribution -- 5.2 Truncated Distributions -- 5.3 Watson Distributions -- 6 Conclusions -- References -- Fast Automatic Bayesian Cubature Using Sobol' Sampling -- 1 Introduction -- 2 Bayesian Cubature -- 3 Digital Nets and Walsh Kernels -- 3.1 Digital Sequences -- 3.2 Covariance Kernels Constructed Via Walsh Functions -- 3.3 Eigenvector-Eigenvalue Decomposition of the Gram Matrix -- 4 Numerical Experiments -- 4.1 Multivariate Gaussian Probability -- 4.2 Keister's Example -- 4.3 Asian Option Pricing -- 4.4 Discussion -- 5 Conclusion and Future Work -- References -- Rendering Along the Hilbert Curve -- 1 Introduction -- 2 Visual Error in Image Synthesis -- 3 Enumerating Pixels Along the Hilbert Curve -- 3.1 Correlation in Space-Filling Curves -- 3.2 Blue-Noise Dithered Sampling -- 4 Progressive Image Synthesis -- 4.1 Deterministic Cranley-Patterson Rotation -- 4.2 Randomization -- 4.3 Contiguous Segments of one Low Discrepancy Sequence -- 4.4 Partitioning one Low Discrepancy Sequence -- 5 Results and Discussion -- 6 Conclusion -- References -- Array-RQMC to Speed up the Simulation for Estimating the Hitting-Time Distribution to a Rare Set of a Regenerative System -- 1 Introduction -- 2 Regenerative-Simulation-Based Estimators of the Distribution of the Hitting Time to a Rarely Visited Set -- 2.1 Assumptions and Notations -- 2.2 Exponential Limit -- 2.3 Exponential Estimators with Monte Carlo (MC) -- 2.4 Convolution Estimators with Monte Carlo. 3 Array-RQMC Implementation of Regenerative-Simulation-Based Estimators of Quantiles -- 3.1 RQMC and Array-RQMC -- 3.2 Array-RQMC Exponential and Convolution Estimators -- 4 Numerical Illustration of the Gain on the Simulation of an M/M/1 Queue -- 5 Conclusions -- References -- Foundations of Ranking & -- Selection for Simulation Optimization -- 1 Introduction -- 2 Set Up -- 3 The Normal Means Case -- 3.1 The Indifference-Zone (IZ) Formulation -- 3.2 R& -- S Based on ``Statistical Learning'' -- 3.3 A Convergence-Rate Perspective -- 3.4 Doing Better Than ``Rate Optimal'' -- 3.5 Common Random Numbers -- 3.6 ``Good Selection'' -- 3.7 Unknown Variances -- 3.8 A Note on Asymptotic Analysis -- 4 Parallel R& -- S -- 4.1 New Measures of Efficiency -- 4.2 New Objectives -- 4.3 Parting Thoughts -- 5 Other Formulations -- 6 Multi-armed Bandits -- References -- Where are the Logs? -- 1 Introduction -- 2 Background -- 3 Proof of the Lower Bound -- 4 Discrepancy and the Case of d equals 1d=1 -- 5 Empirical Investigations for d equals 2d=2 -- 6 Very Large mm for Sobol' Nets -- 7 Discussion -- References -- Network Reliability, Performability Metrics, Rare Events and Standard Monte Carlo -- 1 Introduction -- 2 Performability Metrics and Resilience -- 2.1 The Resilience Metric -- 2.2 Some Properties of Resilience -- 3 Using Standard Monte Carlo for Resilience-Based Analysis -- 3.1 The Standard Estimator -- 3.2 The Standard Estimator Efficiently Implemented in the Rare Event Case -- 3.3 Estimating the Resilience -- 3.4 Improving Algorithm B -- 3.5 Sensitivity Analysis -- 4 Examples and Discussions -- 5 Conclusions -- References. |
Record Nr. | UNINA-9910633937903321 |
Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in modeling and simulation : festschrift for Pierre L'Ecuyer / / Zdravko Botev [and three others], editors |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (426 pages) |
Disciplina | 511.8 |
Soggetto topico |
Mathematical models
Simulation methods Models matemàtics Mètodes de simulació |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-10193-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Biography -- Contents -- Monte Carlo Methods for Pricing American Options -- 1 Introduction -- 2 American Option Pricing -- 3 Binomial Tree Method -- 4 Dynamic Programming Approach -- 4.1 Regression Methods -- 4.2 Malliavin Calculus -- 5 Control Variates -- 6 Numerical Experiments -- 7 Conclusion -- References -- Remarks on Lévy Process Simulation -- 1 Introduction -- 2 Lévy Processes -- 3 Main Examples -- 4 The ε-Algorithm -- 5 Using Complete Monotonicity Structure -- 6 Numerical Examples -- 7 Exact Simulation of X(h) and other Methods -- 8 Maxima, Minima and Other Path Functionals -- References -- Exact Sampling for the Maximum of Infinite Memory Gaussian Processes -- 1 Introduction -- 2 Basic Strategy -- 2.1 Milestone Events -- 2.2 Main Algorithm -- 3 Intermediate Steps in Algorithm 2 -- 4 Analysis of Algorithm 2 -- 4.1 Output Analysis -- 4.2 Complexity Analysis -- 5 Numerical Experiments -- 6 Conclusion -- References -- Truncated Multivariate Student Computations via Exponential Tilting -- 1 Introduction -- 2 Review of the Sequentially Tilted Proposal Density -- 3 Asymptotic Efficiency of the IS Estimator -- 4 Application to Constrained Linear Regression -- 5 Tobit Model Application -- 6 Application to ``Bayesian'' Splines for Non-negative Functions -- 7 The Reject-Regenerate Sampler -- 7.1 Nummelin Splitting of Transition Kernel -- 7.2 Rare-Event Robustness -- 8 Concluding Remarks -- References -- Quasi-Monte Carlo Methods in Portfolio Selection with Many Constraints -- 1 Introduction -- 2 Classical Portfolio Selection in a Nutshell -- 3 Portfolio Optimization with Many Constraints -- 4 Approximation of the Opportunity Set by Naïve Monte Carlo, and by Exponential Monte Carlo -- 5 Approximation of the Opportunity Set with Exponential QMC.
6 Approximating the Market Portfolio with MC, Exponential MC, and Exponential QMC -- 7 Approximating the Whole OS with MC, Exponential MC, and Exponential QMC -- 8 How to Calculate the Dispersion of a Sample Set in an OS? -- 9 Some Simulation Results -- 10 Conclusions, Outlook, and Further Practical Problem -- References -- Geometric-Moment Contraction of G/G/1 Waiting Times -- 1 Introduction -- 2 Main Results -- 3 Monte Carlo Results -- 3.1 M/M/1 Queue -- 3.2 M/G/1 Queues -- 4 Conclusions -- References -- Tractability of Approximation in the Weighted Korobov Space in the Worst-Case Setting -- 1 Introduction -- 2 Basic Definitions -- 2.1 Function Space Setting -- 2.2 Approximation in script upper H Subscript d comma alpha comma bold italic gammamathcalHd,α,γ -- 2.3 The Worst-Case Setting -- 2.4 Useful Relations -- 2.5 Relations to the Average-Case Setting -- 2.6 Notions of Tractability -- 3 The Results for normal upper A normal upper P normal upper P Subscript 2APP2 -- 4 The Results for normal upper A normal upper P normal upper P Subscript normal infinityAPPinfty -- 5 Overview and Formulation of Open Problems -- 5.1 Open Problems -- References -- Rare-Event Simulation via Neural Networks -- 1 Introduction -- 1.1 Background -- 2 Rare-Event Deep Learning -- 2.1 Networks and Loss Functions -- 2.2 Kernel Density Estimation -- 2.3 Training Procedure -- 2.4 Rare-Event Distribution -- 3 Experimental Results -- 3.1 Learning Normal Distributions -- 3.2 Normal Distribution Rare-Events -- 3.3 Learning Sum of Exponential Distributions -- 4 Conclusions and Further Research -- References -- Preintegration is Not Smoothing When Monotonicity Fails -- 1 Introduction -- 1.1 Related Work -- 1.2 The Problem -- 1.3 Informative Examples -- 1.4 Outline of This Paper -- 2 Smoothness Theorems in dd Dimensions -- 3 A High-Dimensional Example -- 4 Conclusion -- References. Combined Derivative Estimators -- 1 Introduction -- 2 Derivative Estimation -- 2.1 Background -- 2.2 Combined Estimators -- 2.3 Second Derivatives -- 2.4 Finite Difference Estimators and IPA -- 2.5 IPA and Randomized Score Functions -- 2.6 LRM Singularities -- 2.7 Generalized Likelihood Ratio Method -- 3 A Barrier Option Example -- 3.1 The Option Pricing Setting -- 3.2 The Barrier Option -- 3.3 A Combined IPA-LRM Estimator of Wang et al. ch10wang -- 3.4 GLR as a Combined IPA-LRM Estimator -- 4 Approaching Continuous Time: Averaging Low-Rank GLR Estimators -- 4.1 Approximating Continuous-Time Sensitivities -- 4.2 Averaging GLR Estimators -- 5 Concluding Remarks -- References -- A Central Limit Theorem For Empirical Quantiles in the Markov Chain Setting -- 1 Introduction -- 2 A Quantile Central Limit Theorem -- 3 A Uniform CLT for 1-Dependent Sequences -- 4 A Quantile Central Limit Theorem for Harris Processes -- 5 The Validity of Non-overlapping Batch-Means Estimation -- 6 Sufficient Conditions -- References -- Simulation of Markov Chains with Continuous State Space by Using Simple Stratified and Sudoku Latin Square Sampling -- 1 Introduction -- 2 Markov Chain Simulation with Stratified Sampling -- 2.1 Classical Monte Carlo -- 2.2 Simple Stratified Sampling -- 2.3 Sudoku Latin Square Sampling -- 3 Variance Bounds -- 3.1 Classical Monte Carlo -- 3.2 Simple Stratified Sampling -- 3.3 Sudoku Latin Square Sampling -- 4 Numerical Experiments -- 4.1 An Autoregressive Process -- 4.2 A European Put Option -- 4.3 Diffusion -- 5 Conclusions -- References -- Quasi-Random Sampling with Black Box or Acceptance-Rejection Inputs -- 1 Introduction -- 2 Methods for the Black Box Setting -- 2.1 Methods Based on the Empirical Quantile Function -- 2.2 Methods Based on a Generalized Pareto Approximation in the Tail -- 3 Combining AR with RQMC. 4 Application: Basket Option Pricing -- 5 Conclusion -- References -- A Generalized Transformed Density Rejection Algorithm -- 1 Introduction -- 2 Transformed Density Rejection with Inflection Points -- 3 Determine Signs of Second Derivatives -- 3.1 Initial Intervals -- 3.2 Splitting Intervals -- 4 The Algorithm -- 5 Applications -- 5.1 Generalized Hyperbolic Distribution -- 5.2 Truncated Distributions -- 5.3 Watson Distributions -- 6 Conclusions -- References -- Fast Automatic Bayesian Cubature Using Sobol' Sampling -- 1 Introduction -- 2 Bayesian Cubature -- 3 Digital Nets and Walsh Kernels -- 3.1 Digital Sequences -- 3.2 Covariance Kernels Constructed Via Walsh Functions -- 3.3 Eigenvector-Eigenvalue Decomposition of the Gram Matrix -- 4 Numerical Experiments -- 4.1 Multivariate Gaussian Probability -- 4.2 Keister's Example -- 4.3 Asian Option Pricing -- 4.4 Discussion -- 5 Conclusion and Future Work -- References -- Rendering Along the Hilbert Curve -- 1 Introduction -- 2 Visual Error in Image Synthesis -- 3 Enumerating Pixels Along the Hilbert Curve -- 3.1 Correlation in Space-Filling Curves -- 3.2 Blue-Noise Dithered Sampling -- 4 Progressive Image Synthesis -- 4.1 Deterministic Cranley-Patterson Rotation -- 4.2 Randomization -- 4.3 Contiguous Segments of one Low Discrepancy Sequence -- 4.4 Partitioning one Low Discrepancy Sequence -- 5 Results and Discussion -- 6 Conclusion -- References -- Array-RQMC to Speed up the Simulation for Estimating the Hitting-Time Distribution to a Rare Set of a Regenerative System -- 1 Introduction -- 2 Regenerative-Simulation-Based Estimators of the Distribution of the Hitting Time to a Rarely Visited Set -- 2.1 Assumptions and Notations -- 2.2 Exponential Limit -- 2.3 Exponential Estimators with Monte Carlo (MC) -- 2.4 Convolution Estimators with Monte Carlo. 3 Array-RQMC Implementation of Regenerative-Simulation-Based Estimators of Quantiles -- 3.1 RQMC and Array-RQMC -- 3.2 Array-RQMC Exponential and Convolution Estimators -- 4 Numerical Illustration of the Gain on the Simulation of an M/M/1 Queue -- 5 Conclusions -- References -- Foundations of Ranking & -- Selection for Simulation Optimization -- 1 Introduction -- 2 Set Up -- 3 The Normal Means Case -- 3.1 The Indifference-Zone (IZ) Formulation -- 3.2 R& -- S Based on ``Statistical Learning'' -- 3.3 A Convergence-Rate Perspective -- 3.4 Doing Better Than ``Rate Optimal'' -- 3.5 Common Random Numbers -- 3.6 ``Good Selection'' -- 3.7 Unknown Variances -- 3.8 A Note on Asymptotic Analysis -- 4 Parallel R& -- S -- 4.1 New Measures of Efficiency -- 4.2 New Objectives -- 4.3 Parting Thoughts -- 5 Other Formulations -- 6 Multi-armed Bandits -- References -- Where are the Logs? -- 1 Introduction -- 2 Background -- 3 Proof of the Lower Bound -- 4 Discrepancy and the Case of d equals 1d=1 -- 5 Empirical Investigations for d equals 2d=2 -- 6 Very Large mm for Sobol' Nets -- 7 Discussion -- References -- Network Reliability, Performability Metrics, Rare Events and Standard Monte Carlo -- 1 Introduction -- 2 Performability Metrics and Resilience -- 2.1 The Resilience Metric -- 2.2 Some Properties of Resilience -- 3 Using Standard Monte Carlo for Resilience-Based Analysis -- 3.1 The Standard Estimator -- 3.2 The Standard Estimator Efficiently Implemented in the Rare Event Case -- 3.3 Estimating the Resilience -- 3.4 Improving Algorithm B -- 3.5 Sensitivity Analysis -- 4 Examples and Discussions -- 5 Conclusions -- References. |
Record Nr. | UNISA-996499866203316 |
Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. di Salerno | ||
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