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Active particles . Volume 3 : advances in theory, models, and applications / / Nicola Bellomo, José Antonio Carrillo, and Eitan Tadmor, editors
| 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] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Addressing Modern Challenges in the Mathematical, Statistical, and Computational Sciences : The VI AMMCS International Conference, Waterloo, Canada, August 14–18, 2023 / / edited by D. Marc Kilgour, Herb Kunze, Roman N. Makarov, Roderick Melnik, Xu Wang
| Addressing Modern Challenges in the Mathematical, Statistical, and Computational Sciences : The VI AMMCS International Conference, Waterloo, Canada, August 14–18, 2023 / / edited by D. Marc Kilgour, Herb Kunze, Roman N. Makarov, Roderick Melnik, Xu Wang |
| Autore | Kilgour D. Marc |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (913 pages) |
| Disciplina | 519 |
| Altri autori (Persone) |
KunzeHerb
MakarovRoman N MelnikRoderick WangXu |
| Collana | Springer Proceedings in Mathematics & Statistics |
| Soggetto topico |
Mathematics
Mathematical models Engineering mathematics Engineering - Data processing Social sciences Artificial intelligence - Data processing Biomathematics Applications of Mathematics Mathematical Modeling and Industrial Mathematics Mathematical and Computational Engineering Applications Mathematics in the Humanities and Social Sciences Data Science Mathematical and Computational Biology Estadística matemàtica Models matemàtics |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031848698
9783031848681 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | PartI:Advances in Mathematical Modelling and Theory -- The Study of the Transformation Semigroup of the Abelian and Directed Non-Abelian Sandpiles -- On Constructing Finite Automata by Relational Programming -- Skeleton Key: Subduction Classes in Finite Transformation Semigroups and Green’s Relations -- The Attractor-Cycle Notation for Finite Transformations -- Algebraic Applications in Investigation of Musical Symmetry -- Analysis of the Semigroup Related to the Petri Net of a Traffic Roundabout.-PartII:Innovations in Statistical Machine Learning and Stochastic Models -- From Interval-valued Neurons to Convex-polygon-valued Neurons, with Sparsity and Entropy Criteria -- Excursions of Solvable Scalar Diffusions -- Hybrid Impulsive Formation Control of Vehicle Platoons Using Neural Networks -- Pinning impulsive control for synchronization of complex-valued delayed multilayer networks -- Quasi-synchronization of fractional-order multiplex networks with parameter mismatch via intermittent control -- Part III: Mathematical Modelling in Engineering, Physical and Chemical Sciences -- An Optimization-based Approach to Image Fusion using Structural Similarity -- Hamiltonian engineering with time-ordered evolution for unitary control of electron spins in semiconductor quantum dots -- Exploring the use of gradients in the Structural Similarity image quality measure -- Simulated Charge Stability in a MOSFET Linear Quantum Dot Array -- Vreman Stabilization for Nonlinear Greenshield’s Model for Traffic Flow -- Computational Modelling of Heat Transport in Kinked Nanowires -- Telling Oil Temperature for Frying from Audio and Video Signals based on Multimodal Learning -- Gravitational Models with State-Dependent Delay: Gravitating Binaries -- Self-similar Heat Transfer in a Turbulent Particle-laden Free Flow -- A Tire Side Slip Model with Dynamic Friction Distribution over the Contact Patch -- Part IV: Mathematical and Statistical Modelling in Biological, Medical and Health Sciences -- Stability and Qualitative Analysis of a Switched SQEIAR- Based Epidemic Model -- The Influence of Refuges, Fear, and Velocities on Predator-prey Dynamics -- A Multiscale Model for Protein Allostery: Side Chain Concerted Motions Initiated by Brownian Kicks -- Near-soma Activated Action Potential in Gonadotropin-releasing Hormone Neurons -- Modeling Patterns of Sex-Dependent Neuroprotection Loss in Alzheimer’s Disease -- Deciphering heterogeneity of ATP-induced Ca2+ responses in osteoblasts using the flux-balance model -- Parameter Estimation of Hodgkin-Huxley Model: A Comparative Study of Genetic Algorithm and Artificial Neural Network Approach -- PartV: Mathematics and Computation in Finance, Economics, and Social Sciences -- Credit Risk Modelling with Occupation Times under Nonlinear Local Volatility Models -- Financial News Headlines Sentiment Analysis Enhances Stock Market Prediction -- Self-Exciting Point Processes in Real Estate -- Algebraic Structure and Complexity of Games -- State-Complexity Relations in Evolved Players of the Iterated Prisoners’ Dilemma -- The Sparse Grid Combination Method for Multidimensional Black-Scholes Partial Differential Equations -- PartVI: Theory and Computational Methods for Differential Equations -- Input-to-state stability for cascaded impulsive systems and H∞control -- Time Filtered Finite Difference Schemes for Linear Hyperbolic Problems -- Computational Considerations for Implementing the Collage Method for ODE Inverse Problems -- Penalty Ensembles for Navier-Stokes with Random Initial Conditions & Forcing -- Explicit Periodic Solutions in a Delay Differential Equation -- Proportional Consistency of Apportionment Methods -- Observer-Based Adaptive Robust Fractional Order Control of a class of Nonlinear Delayed Constrained Systems with Singularity -- Stability criteria of a class of nonlinear impulsive neutral swithcing systems -- pythOS: An operator-splitting library in Python -- Sensitivity and Optimal Control Theory for Linear Complementarity Systems -- History of an Oscillation Criterion for First-Order Delay Differential Equations -- Observer and Command Filter-Based Prescribed Performance Control for a Class of onlinear Systems with Mismatched Disturbances. |
| Record Nr. | UNINA-9911021966403321 |
Kilgour D. Marc
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Mathematical Science for Mobility Society / / edited by Kazushi Ikeda, Yoshiumi Kawamura, Kazuhisa Makino, Satoshi Tsujimoto, Nobuo Yamashita, Shintaro Yoshizawa, Hanna Sumita
| Advanced Mathematical Science for Mobility Society / / edited by Kazushi Ikeda, Yoshiumi Kawamura, Kazuhisa Makino, Satoshi Tsujimoto, Nobuo Yamashita, Shintaro Yoshizawa, Hanna Sumita |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (VIII, 215 p. 52 illus., 40 illus. in color.) |
| Disciplina | 004.0151 |
| Soggetto topico |
Computer science
Mathematical models Quantitative research Transportation engineering Traffic engineering Theory and Algorithms for Application Domains Mathematical Modeling and Industrial Mathematics Data Analysis and Big Data Transportation Technology and Traffic Engineering Informàtica Models matemàtics Investigació quantitativa Enginyeria del trànsit |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-9997-72-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1. Introduction, motivation, and direction for Advanced Mathematical Science for Mobility Society, together with the project between Toyota Motor Corporation and Kyoto University -- Chapter 1. Advanced Mathematical Science for Mobility Society -- Part 2. Mathematical models of flow Chapter. 2. Analysis of many-body particle systems by geometry and box-ball-system theory -- Chapter 3. Discrete Integrable Systems, LR transformations and Box-Ball Systems -- Part 3. Mathematical methods for huge data and network analysis -- Chapter 4. Eigenvalue Analysis in Mobility Data -- Chapter 5. Application of tensor network formalism for processing tensor data -- Chapter 6. Machine Learning Approach to Mobility Analysis -- Chapter 7. Graph optimization problems and algorithms for DAG-type blockchains -- Part 4. Algorithm for mobility society -- Chapter 8. Control and optimization of one-way car-sharing systems -- Chapter 9. Algorithms for future mobility society Chapter 10. Mechanism Design for Mobility. |
| Record Nr. | UNINA-9910845080703321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| 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
| 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] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advances in fuzzy group decision making / / Tin-Chih Toly Chen
| 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 |
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Chen Toly <1969->
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advances in modeling and simulation : festschrift for Pierre L'Ecuyer / / Zdravko Botev [and three others], editors
| 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] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Algorithms for a New World [[electronic resource] ] : When Big Data and Mathematical Models Meet / / by Alfio Quarteroni
| Algorithms for a New World [[electronic resource] ] : When Big Data and Mathematical Models Meet / / by Alfio Quarteroni |
| Autore | Quarteroni Alfio |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (68 pages) : illustrations |
| Disciplina | 006.3 |
| Soggetto topico |
Mathematics
Machine learning Artificial intelligence Quantitative research Algorithms Applications of Mathematics Machine Learning Artificial Intelligence Data Analysis and Big Data Models matemàtics Intel·ligència artificial Dades massives |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783030961664
9783030961657 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Epidemic -- 2 Retrospective -- 3 Interlude: the revolution that did not happen and the revolution that was unforeseen -- 4 Artificial intelligence, learning computers, artificial neural networks -- 5 A bit of maths (behind artificial intelligence and machine learning) -- 6 BIG DATA - BIG BROTHER (or, on the ethical and moral aspects of artificial intelligence). |
| Record Nr. | UNISA-996483155303316 |
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Quarteroni Alfio
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Analysis and design of nonlinear systems in the frequency domain / / Yunpeng Zhu
| Analysis and design of nonlinear systems in the frequency domain / / Yunpeng Zhu |
| Autore | Zhu Yunpeng |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xxi, 164 pages) : illustrations |
| Disciplina | 003.75 |
| Collana | Springer Theses, Recognizing Outstanding Ph.D. Research |
| Soggetto topico |
Nonlinear systems - Mathematical models
Volterra equations Sistemes no lineals Models matemàtics Equacions de Volterra |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-70833-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Supervisor's Foreword -- Preface -- Acknowledgements -- Contents -- Contributors -- Abbreviations -- 1 Introduction -- 1.1 Background -- 1.1.1 Modelling of Nonlinear Systems -- 1.1.2 Frequency Domain Analysis and Design of Nonlinear Systems -- 1.1.3 LS Methods in Nonlinear System Analyses -- 1.1.4 Convergence Issues with the Frequency Analysis of Nonlinear Systems -- 1.2 Aim, Objectives and Contributions -- 1.3 Thesis Layout -- References -- 2 Nonlinear Systems and the Frequency Domain Representations -- 2.1 Introduction -- 2.2 Polynomial Models of Nonlinear Systems -- 2.2.1 The NDE Model of Nonlinear Systems -- 2.2.2 The Polynomial NARX Model of Nonlinear Systems -- 2.2.3 The NARX-M-for-D of Nonlinear Systems -- 2.3 The Frequency Domain Representations of Nonlinear Systems -- 2.3.1 The Volterra Series Representation -- 2.3.2 The Generalised Frequency Response Functions (GFRFs) of Nonlinear Systems -- 2.3.3 The Nonlinear Output Frequency Response Functions (NOFRFs) of Nonlinear Systems -- 2.3.4 The Output Frequency Response Function (OFRF) of Nonlinear Systems -- 2.4 Conclusions -- References -- 3 Generalized Associated Linear Equations (GALEs) with Applications to Nonlinear System Analyses -- 3.1 Introduction -- 3.2 The Associated Linear Equations (ALEs) of Nonlinear Systems -- 3.2.1 The ALEs of Duffing Equations -- 3.2.2 The ALEs of the NARX Model -- 3.3 The Generalized Associated Linear Equations (GALEs) -- 3.3.1 The Concept of the GALEs -- 3.3.2 Determination of the GALEs -- 3.4 System Analyses Using the GALEs -- 3.4.1 Evaluation of the Output Response of Nonlinear Systems -- 3.4.2 Evaluation of the NOFRFs of Nonlinear Systems -- 3.4.3 Evaluation of the OFRF of Nonlinear Systems -- 3.5 Application of the GALEs to Nonlinear System Modelling, Fault Diagnosis, and Design.
3.5.1 Application to the Identification of the NDE Model of a Nonlinear System -- 3.5.2 Application to the NOFRFs Based Fault Diagnosis -- 3.5.3 Application to the OFRFs Based Design of Nonlinear Energy Harvester Systems -- 3.6 Conclusions -- References -- 4 The Convergence of the Volterra Series Representation of Nonlinear Systems -- 4.1 Introduction -- 4.2 The NARX Model in the Frequency Domain: Nonlinear Output Characteristic Spectra (NOCS) Model -- 4.3 The Generalized Output Bound Characteristic Function (GOBCF) Based Convergence Analysis -- 4.3.1 A Sufficient Condition of the Convergence -- 4.3.2 The Determination of the GOBCF -- 4.3.3 Convergence Analysis of the Volterra Series Representation of Nonlinear Systems -- 4.3.4 The Procedure for the New Convergence Analysis -- 4.4 Case Studies -- 4.4.1 Case 1-Unplugged Van der Pol Equation -- 4.4.2 Case 2-Duffing Oscillator with Cubic Damping -- 4.5 Conclusions -- References -- 5 The Effects of Both Linear and Nonlinear Characteristic Parameters on the Output Response of Nonlinear Systems -- 5.1 Introduction -- 5.2 The OFRF Based Design of NARX-M-for-D -- 5.2.1 The OFRF of the NARX-M-for-D -- 5.2.2 The Determination of the OFRF of NARX-M-for-D -- 5.2.3 The OFRF Based Design of Nonlinear Systems -- 5.3 The Associated Output Frequency Response Function (AOFRF) -- 5.3.1 Explicit Relationships Between the GFRFs and the Parameters of the NARX Model -- 5.3.2 Two Special Cases -- 5.3.3 The Concept of the Associated Output Frequency Response Function (AOFRF) -- 5.3.4 The AOFRF in Terms of the System Linear and Nonlinear Characteristic Parameters -- 5.3.5 The AOFRF Based Representation of the Output Frequency Response of Nonlinear Systems -- 5.4 Case Studies -- 5.4.1 Case Study 1-The OFRF Based Design of the Vibration Isolation System. 5.4.2 Case Study 2-The AOFRF Based Representation of the Output Spectrum of a Duffing Nonlinear System -- 5.5 Conclusions -- References -- 6 Nonlinear Damping Based Semi-active Building Isolation System -- 6.1 Introduction -- 6.2 Semi-active Damping System for the Sosokan Building -- 6.2.1 The Sosokan Building and Its Model Representation -- 6.2.2 Semi-active Damping System for the Sosokan Building -- 6.3 Nonlinear Damping Based Semi-active Building Vibration Isolation -- 6.4 Simulation Studies -- 6.4.1 Objectives of Nonlinear Damping Design -- 6.4.2 Effects of Nonlinear Damping Coefficient -- 6.4.3 Effects of Ground Excitation Magnitude -- 6.4.4 Isolation Performance on Higher Floors -- 6.4.5 Isolation Performance in Terms of the Roof Drift -- 6.4.6 Isolation Performance in Terms of Harmonics and a Comparison with the Performance Under LQG Control -- 6.5 Experimental Validation -- 6.6 Conclusions -- References -- 7 Conclusions -- 7.1 Main Contributions of the Present Research -- 7.2 Future Works -- Appendix A Sampling Frequency Independence -- Appendix B Proof of Lemma 5.1. |
| Record Nr. | UNINA-9910484062803321 |
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Zhu Yunpeng
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Analysis of infectious disease problems (Covid-19) and their global impact / / Praveen Agarwal [and three others], editors
| Analysis of infectious disease problems (Covid-19) and their global impact / / Praveen Agarwal [and three others], editors |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (635 pages) |
| Disciplina | 616.241400285 |
| Collana | Infosys Science Foundation series in mathematical sciences |
| Soggetto topico |
COVID-19
Models matemàtics COVID-19 (Disease) - Mathematical models |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-16-2450-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- General Analysis -- Continued and Serious Lockdown Could Have Minimized Many Newly Transmitted Cases of Covid-19 in the U.S.: Wavelets, Deterministic Models, and Data -- 1 Introduction -- 2 Methods, Models and Data -- 3 Data -- 4 Results -- 5 Concluding Remarks -- References -- Dynamical Analysis of a Caputo Fractional Order SIR Epidemic Model with a General Treatment Function -- 1 Introduction -- 2 Mathematical Model and Preliminaries -- 3 Preliminaries -- 4 The Well-Posedness of the Model and Equilibria -- 4.1 Existence of Endemic Equilibrium -- 5 Local Stability Analysis -- 6 Global Stability Analysis -- 6.1 Infection-Free Equilibrium -- 6.2 Endemic Equilibrium -- 7 Numerical Simulations -- 8 Concluding Remarks -- References -- Protective Face Shield Effectiveness: Mathematical Modelling -- 1 Introduction -- 2 Practical Application of Face Shields -- 3 Mathematical Modelling -- 3.1 Euler Form of Equations -- 3.2 Lagrangian Form of Equations -- 3.3 Model Description -- 3.4 Numerical Methods -- 3.5 Computer Simulation -- 4 Full-Scale Experiment -- 5 Conclusion -- References -- On the Evolution Equation for Modelling the Covid-19 Pandemic -- 1 Introduction -- 2 The Evolution Equation -- 2.1 The Classical Kolmogorov-Feller Equation -- 2.2 The Generalised Kolmogorov-Feller Equation -- 2.3 Orthonormal Memory Functions -- 2.4 Time Series Models -- 2.5 Logarithmic Scale Analysis -- 3 Random Walk Fields -- 4 Self-Affine Random Walk Fields -- 4.1 Solution for Eq. (7) -- 4.2 Solution for Eq. (8) -- 4.3 Random Walk Analysis -- 4.4 Example Results -- 5 The Bio-Dynamics Hypothesis -- 5.1 Self-affine Structures of a Virus -- 5.2 A Parametric Self-affine Model -- 5.3 Discussion -- 6 Summary, Conclusions and Future Research -- 6.1 Summary -- 6.2 Conclusions -- 6.3 Future Research.
References -- Modelling the Dynamics of Fake News Spreading Transmission During Covid-19 Through Social Media -- 1 Introduction -- 2 Methodology/Proposal -- 2.1 SIR Model for Fake News Transmission -- 2.2 Fake News Transmission Rate Through Different Social Media Platforms -- 2.3 Fake News Transmission Rate Among Users of Different Age Groups -- 2.4 Fake News Transmission Rate Among Users of Facebook from Different Countries -- 3 Results, Interpretation and Discussion -- 4 Conclusion -- References -- Generalized Logistic Equations in Covid-Related Epidemic Models -- 1 Introduction -- 2 Logistic Coefficients Models -- 2.1 Computable Examples -- 3 Carrying Capacity Periodically Variable -- 3.1 Existence of Periodic Solution -- 3.2 Cosinusoidal Carrying Capacity -- 4 Periodic Harvesting -- 4.1 Global Features of the Solution -- 4.2 Closed-Form Integration and Examples -- 4.3 A Sample Problem -- References -- A Transition of Shared Mobility in Metro Cities-A Challenge Post-Lockdown Covid-19 -- 1 Introduction -- 2 BPR Model -- 3 Data Analysis & -- Implementation -- 3.1 Data Description -- 3.2 Model Application & -- Results -- 3.3 Prediction of Traffic Scenarios Post-Lockdown -- 4 India's Transport Growth Journey and Its Effect on Energy and Environment -- 4.1 Transport and Environment -- 4.2 Health and Social Issues -- 4.3 Personal Vehicles and Their Impact -- 4.4 Measures to Curb the Traffic Upsurge -- References -- Analysis of Covid-19 Virus Spreading Statistics by the Use of a New Modified Weibull Distribution -- 1 Introduction and Preliminaries -- 1.1 The New Model NMWB Distribution -- 1.2 The Reliability Function -- 1.3 Moments of the Distribution -- 1.4 Order Statistics -- 1.5 Parameter Estimation -- 1.6 Relationship with Weibull-Related Results -- 2 Main Results -- 2.1 Statistical Properties -- 2.2 Least Square Estimates (LSES). 2.3 Order Statistics -- 2.4 Parameter Estimation -- 3 Applications -- 4 Conclusion -- References -- Lifting Lockdown Control Measure Assessment: From Finite-to Infinite-Dimensional Epidemic Models for Covid-19 -- 1 Introduction -- 2 Data Collection -- 3 Basic Covid-19 Model -- 3.1 Reproduction Numbers -- 3.2 Parameter and Initial Data Estimation -- 4 Discrete Age-Structured Covid-19 Model -- 4.1 Reproduction Numbers -- 4.2 Parameter and Initial Data Estimation -- 5 Covid-19 Model with Constant Delay -- 5.1 Reproduction Numbers -- 5.2 Parameter and Initial Data Estimation -- 6 Covid-19 Model with Threshold-Type Delay -- 7 Models with Demographic Effects -- 7.1 Covid-19 Model with Constant Delay -- 7.2 Covid-19 Model with Threshold-Type Delay -- 8 Discussion -- References -- Introduction to the Grey Systems Theory and Its Application in Mathematical Modeling and Pandemic Prediction of Covid-19 -- 1 A Brief Introduction to the Grey Systems Theory -- 2 Description of the Traditional Linear and Nonlinear Univariate Grey Models GM(1, 1) and NGBM(1, 1) -- 2.1 Building the Traditional Grey Model GM(1, 1) -- 2.2 The Nonlinear Grey Bernoulli Model NGBM(1, 1) -- 3 Optimization of the Univariate Grey Models -- 3.1 Optimization of Hyper-parameters -- 3.2 Rolling Mechanism -- 3.3 Optimization of the Initial Condition -- 4 Applications of Univariate Grey Models in Predicting Total Covid-19 Infected Cases -- 5 Description of the Existing GM(1, N) and GMC(1, N) Models -- 5.1 The Traditional GM(1, N) Model -- 5.2 The Grey Model with Convolution Integral GMC(1, N) -- 5.3 Variations of the Current GMC(1, N) and GMC(1, N) Models -- 5.4 Representation of the Nonlinear Grey Model with Convolution Integral NGMC(1, N) -- 6 Grey System Models with Fractional Order Accumulation -- 6.1 Definition of the Fractional Order Accumulation -- 6.2 The Fractional GMpq(1, 1) Model. 6.3 The Fractional Multivariate Grey Model with Convolutional Integral GMC pq(1, N) -- 6.4 Optimization of the Fractional Order r -- 7 Introduction to the Grey Relational Analysis -- 7.1 Data Preprocessing -- 7.2 Grey Relational Coefficient and Grey Relational Grade -- 8 Applications of Grey Relational Analysis In medicine -- 8.1 General Applications of Grey Relational Analysis in Medical Data Analysis -- 8.2 Application in Telecare -- 8.3 Grey Data Management in Medicine -- References -- Mathematical Analysis of Diagnosis Rate Effects in Covid-19 Transmission Dynamics with Optimal Control -- 1 Introduction -- 2 Model Formulation -- 3 Mathematical Analysis -- 3.1 The Disease-Free Equilibrium and Control Reproduction Number -- 3.2 Global Stability of DFE -- 3.3 Existence and Local Stability of the Endemic Equilibrium -- 3.4 Sensitivity Analysis -- 3.5 Numerical Simulation -- 4 Optimal Control -- 4.1 Building the Optimal Control Problem -- 4.2 Characterization of the Optimal Control -- 4.3 Numerical Simulation of the Optimal Control Problem -- 5 Conclusion -- References -- Development of Epidemiological Modeling RD-Covid-19 of Coronavirus Infectious Disease and Its Numerical Simulation -- 1 Introduction -- 2 Infectious Disease Epidemiology Components -- 2.1 Timelines of Infection -- 2.2 Estimation of Transmission Probability -- 2.3 The SAR is a Proportion, Not a Rate -- 3 Estimation of Basic Reproduction Number/ Proliferation Number -- 3.1 Estimation of R0 -- 3.2 Virulence of R0 and the Case Fatality Ratio (CFR) -- 4 Incidence Rate as a Function of Prevalence and Contact Rate -- 5 Dynamic Epidemic Process in a Closed Population -- 6 RD-Covid-19 Epidemiological Model -- 7 Numerical Simulation of RD-Covid-19 Model -- 7.1 PART-1: Numerical Outcome of RD-Covid-19 Model Outcome for INDIA. 7.2 PART-2: Numerical Outcome of RD-Covid-19 Model Outcome for CHINA -- 7.3 PART-3: Numerical Outcome of RD-Covid-19 Model Outcome for BRAZIL -- 7.4 PART-4: Numerical Outcome of RD-Covid-19 Model Outcome for RUSSIA -- 8 Conclusions -- References -- Mediterranean Diet-A Healthy Dietary Pattern and Lifestyle for Strong Immunity -- 1 Introduction -- 2 Mediterranean Lifestyle -- 3 Benefits of Mediterranean Diet -- 4 Mediterranean Diet for a Healthy Gut -- 5 Conclusion -- References -- Rate-Induced Tipping Phenomena in Compartment Models of Epidemics -- 1 Introduction -- 1.1 Outline -- 2 Preliminaries -- 2.1 Compartment Models with Time-Dependent Parameters -- 2.2 Autonomous SIR Model -- 2.3 Autonomous SIRS Model -- 3 Linear Compartment Models -- 3.1 Artifacts of Rate-Induced Tipping -- 4 Nonlinear Compartment Models -- 4.1 Local Normal Form for a Bifurcation of Codimension Two -- 4.2 Idealized Models -- 5 Irreducible Rate-Induced Tipping in Non-autonomous Models -- 5.1 Artifacts of Rate-Induced Tipping -- 6 Conclusion -- References -- Analysis of Impact of Covid-19 Pandemic on Financial Markets -- 1 Introduction -- 2 Market Behaviour During Initial and Intermediate Pandemic Phases -- 2.1 Covid-19 Market Crash (2020/02/19-2020/03/19) -- 2.2 Market Recovery After Covid-19 Crash (2020/03/20 - 2020/03/26) -- 2.3 Pandemic Growth After 2020/03/18 -- 3 Framework for Modelling Pandemic Impact -- 3.1 Susceptible, Infected, Recovered and Death (SIRD) Model with Time-Dependent Parameters and Social Distancing -- 3.2 Calibration Algorithm -- 3.3 Phenomenological Pandemic Model (PPM) -- 3.4 The Process N(t) in an Intermediate Phase -- 3.5 Approximation to PPM -- 3.6 Calibration of PPM -- 3.7 Mapping Epidemic Variables to Financial Risk Factors -- 4 Simulation of Stress Scenarios -- 4.1 Simulation of Risk Drivers Under the SIRD Model -- 4.2 PPM Simulation. 5 Conclusion. |
| Record Nr. | UNISA-996466401503316 |
| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Analysis of reaction-diffusion models with the Taxis mechanism / / Yuanyuan Ke, Jing Li, Yifu Wang
| Analysis of reaction-diffusion models with the Taxis mechanism / / Yuanyuan Ke, Jing Li, Yifu Wang |
| Autore | Ke Yuanyuan |
| Pubbl/distr/stampa | Singapore, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (ix, 411 pages) : illustrations (some color) |
| Altri autori (Persone) |
LiJing WangYifu |
| Collana | Financial Mathematics and Fintech |
| Soggetto topico |
Boundary value problems
Chemotaxis - Mathematical models Navier-Stokes equations Problemes de contorn Quimiotaxi Models matemàtics Equacions de Navier-Stokes |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Reaction-Diffusion
Chemotaxis Haptotaxis Navier-Stokes Cancer invasion Coral fertilization Sensity-suppressed motility Oncolytic virotherapy Foraging scrounging interplay |
| ISBN | 981-19-3763-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Large time behavior of solutions to the chemotaxis-fluid Chapter 2. Global existence in Keller Segel Navier Stokes system involving tensor-valued sensitivity Chapter 3. Large time behavior of solutions to chemotaxis haptotaxis models Chapter 4. Large time behavior of Keller Segel (Navier) Stokes system modeling coral fertilization Chapter 5. Qualitative properties to density-suppressed motility models Chapter 6. Large time behavior of multi-taxis cross-diffusion system |
| Record Nr. | UNISA-996485660903316 |
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Ke Yuanyuan
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| Singapore, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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