LEADER 11006nam 2200589 450 001 996466393103316 005 20231110225150.0 010 $a3-030-72983-4 035 $a(CKB)4100000012009056 035 $a(MiAaPQ)EBC6712971 035 $a(Au-PeEL)EBL6712971 035 $a(OCoLC)1265465325 035 $a(PPN)257350977 035 $a(EXLCZ)994100000012009056 100 $a20220605d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aModel reduction of complex dynamical systems /$fPeter Benner [and five others] 210 1$aCham, Switzerland :$cSpringer International Publishing,$d[2021] 210 4$d©2021 215 $a1 online resource (416 pages) 225 1 $aInternational Series of Numerical Mathematics ;$vv.171 311 $a3-030-72982-6 327 $aIntro -- Preface -- Contents -- *-20pt Methods and Techniques of Model Order Reduction -- On Bilinear Time-Domain Identification and Reduction in the Loewner Framework -- 1 Introduction -- 1.1 Outline of the Paper -- 2 System Theory Preliminaries -- 2.1 Linear Systems -- 2.2 Nonlinear Systems -- 3 The Loewner Framework -- 3.1 The Loewner Matrix -- 3.2 Construction of Interpolants -- 4 The Special Case of Bilinear Systems -- 4.1 The Growing Exponential Approach -- 4.2 The Kernel Separation Method -- 4.3 Identification of the Matrix N -- 4.4 A Separation Strategy for the second Kernel -- 4.5 The Loewner-Volterra Algorithm for Time-Domain Bilinear Identification and Reduction -- 4.6 Computational Effort of the Proposed Method -- 5 Numerical Examples -- 6 Conclusion -- References -- Balanced Truncation for Parametric Linear Systems Using Interpolation of Gramians: A Comparison of Algebraic and Geometric Approaches -- 1 Introduction -- 2 Balanced Truncation for Parametric Linear Systems and Standard Interpolation -- 2.1 Balanced Truncation -- 2.2 Interpolation of Gramians for Parametric Model Order Reduction -- 2.3 Offline-Online Decomposition -- 3 Interpolation on the Manifold mathcalS+(k,n) -- 3.1 A Quotient Geometry of mathcalS+(k,n) -- 3.2 Curve and Surface Interpolation on Manifolds -- 4 Numerical Examples -- 4.1 A model for heat conduction in solid material -- 4.2 An Anemometer Model -- 5 Conclusion -- References -- Toward Fitting Structured Nonlinear Systems by Means of Dynamic Mode Decomposition -- 1 Introduction -- 2 Dynamic Mode Decomposition -- 2.1 Dynamic Mode Decomposition with Control (DMDc) -- 2.2 Input-Output Dynamic Mode Decomposition -- 3 The Proposed Extensions -- 3.1 Bilinear Systems -- 3.2 Quadratic-Bilinear Systems -- 4 Numerical Experiments -- 4.1 The Viscous Burgers' Equation -- 4.2 Coupled van der Pol Oscillators. 327 $a5 Conclusion -- 6 Appendix -- 6.1 Computation of the Reduced-Order Matrices for the Quadratic-Bilinear Case -- References -- Clustering-Based Model Order Reduction for Nonlinear Network Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 Graph Theory -- 2.2 Graph Partitions -- 2.3 Linear Multi-agent Systems -- 2.4 Clustering-Based Model Order Reduction -- 2.5 Model Reduction for Non-asymptotically Stable Systems -- 3 Clustering for Linear Multi-agent Systems -- 4 Clustering for Nonlinear Multi-agent Systems -- 4.1 Nonlinear Multi-agent Systems -- 4.2 Clustering by Projection -- 5 Numerical Examples -- 5.1 Small Network Example -- 5.2 van der Pol Oscillators -- 6 Conclusions -- References -- Adaptive Interpolatory MOR by Learning the Error Estimator in the Parameter Domain -- 1 Introduction -- 2 Interpolatory MOR -- 3 Greedy Method for Choosing Interpolation Points -- 4 Adaptive Training by Learning the Error Estimator in the Parameter Domain -- 4.1 Radial Basis Functions -- 4.2 Learning the Error Estimator over the Parameter Domain -- 4.3 Adaptive Choice of Interpolation Points with Surrogate Error Estimator -- 5 Numerical Examples -- 5.1 RLC Interconnect Circuit -- 5.2 Thermal Model -- 5.3 Dual-Mode Circular Waveguide Filter -- 6 Conclusion -- References -- A Link Between Gramian-Based Model Order Reduction and Moment Matching -- 1 Introduction -- 1.1 Balancing of LTI Systems -- 1.2 Rational Interpolation -- 1.3 Organization of Paper -- 2 Gramian Quadrature Algorithm -- 2.1 Approximating the Gramian via Runge-Kutta Methods -- 2.2 Computation of mathcalHj in Algorithm 1 -- 2.3 The Space Spanned by the Approximate Cholesky Factor Z -- 3 Approximate Balancing Transformation -- 4 Connection to Other Methods -- 4.1 Balanced POD -- 4.2 The ADI Iteration -- 5 Examples -- 6 Conclusion -- References. 327 $aComparing (Empirical-Gramian-Based) Model Order Reduction Algorithms -- 1 Introduction -- 2 Empirical Gramians for Linear Systems -- 2.1 Empirical Controllability Gramian -- 2.2 Empirical Observability Gramian -- 2.3 Empirical Cross Gramian -- 2.4 Parametric Empirical Gramians -- 3 Empirical-Gramian-Based Model Reduction -- 3.1 Empirical Poor Man -- 3.2 Empirical Approximate Balancing -- 3.3 Empirical Dominant Subspaces -- 3.4 Empirical Balanced Truncation -- 3.5 Empirical Balanced Gains -- 4 Approximate Norms -- 4.1 Signal Norms -- 4.2 System Norms -- 4.3 Modified Induced Norms -- 4.4 Parametric Norms -- 5 MORscore -- 6 Benchmark Comparison -- 6.1 emgr - EMpirical GRamian Framework -- 6.2 Thermal Block Benchmark -- 6.3 Numerical Results -- 7 Conclusion -- References -- Optimization-Based Parametric Model Order Reduction for the Application to the Frequency-Domain Analysis of Complex Systems -- 1 Introduction -- 2 Basics of the Global Basis and Krylov Subspace Method -- 2.1 Krylov Subspaces -- 2.2 Affine Matrix Decomposition -- 3 OGPA: Optimization-based Greedy Parameter Sampling -- 3.1 Grid-Free Sampling -- 3.2 A-Posteriori Model Quality Evaluation -- 4 Numerical Examples -- 4.1 Cantilever Solid Beam -- 4.2 Rear Axle Carrier -- 5 Summary -- References -- On Extended Model Order Reduction for Linear Time Delay Systems -- 1 Introduction -- 2 Problem Statement -- 3 Observability and Controllability Inequalities -- 4 Model order reduction by truncation -- 5 Feasibility of the Matrix Inequalities -- 6 Example: Delay Neural Fields -- 7 Application to Parameterized Model Reduction -- 7.1 Example -- 8 Conclusions -- References -- *-20pt Applications of Model Order Reduction -- A Practical Method for the Reductionpg of Linear Thermo-Mechanical Dynamic Equations -- 1 Introduction -- 2 The Thermo-Mechanical Model -- 2.1 Structural Mechanics. 327 $a2.2 Heat Transfer -- 2.3 Coupling of Equations -- 3 Derivation of the Reduction Algorithm -- 3.1 Model Order Reduction -- 3.2 Extraction of the Coupling Matrix -- 3.3 Algorithm -- 4 Implementation and Results -- 4.1 Modeling -- 4.2 Results -- 5 Conclusions -- References -- Reduced-Order Methods in Medical Imaging -- 1 Introduction -- 2 Methods -- 2.1 Medical Tomography -- 2.2 Proper Orthogonal Decomposition -- 2.3 Downsampled POD Method -- 2.4 Hybrid-POD Method -- 2.5 Implementation Details -- 3 Results -- 3.1 Test Tube with Fish Eggs -- 3.2 Down-Sampling Results -- 3.3 Hybrid-POD Method -- 4 Discussion -- 5 Conclusion -- References -- Efficient Krylov Subspace Techniques for Model Order Reduction of Automotive Structures in Vibroacoustic Applications -- 1 Introduction -- 2 Krylov-Based Model Order Reduction -- 2.1 Problem Definition -- 2.2 Reduction Framework -- 3 Numerical Implementation -- 4 Results -- 4.1 Generic System -- 4.2 Coupled System -- 5 Conclusions and Remarks -- References -- Model-Based Adaptive MOR Framework for Unsteady Flows Around Lifting Bodies -- 1 Introduction -- 2 Linear Reduced Basis Methods -- 3 Adaptive Approach -- 3.1 Physical Problem: Navier-Stokes Equations -- 3.2 Error Estimation -- 3.3 Sensitivity -- 4 Demonstration on Lifting Surfaces -- 4.1 Stalled NACA0012 Airfoil -- 4.2 High-Lift 30P30N Airfoil -- 5 Final Remarks and Outlook -- References -- Reduced Basis Methods for Quasilinear Elliptic PDEs with Applications to Permanent Magnet Synchronous Motors -- 1 Introduction -- 2 The Quasilinear Parametric Elliptic PDE -- 2.1 Abstract Formulation -- 3 Reduced Basis Approximation -- 3.1 An EIM-RB Method -- 3.2 Error Estimation -- 3.3 Computational Procedure -- 3.4 Numerical Results -- 4 Conclusion -- References -- Structure-Preserving Reduced- Order Modeling of Non-Traditional Shallow Water Equation -- 1 Introduction. 327 $a2 Shallow Water Equation -- 3 Full- Order Model -- 4 Reduced- Order Model -- 5 Numerical Results -- 5.1 Single-Layer Geostrophic Adjustment -- 5.2 Single-Layer Shear Instability -- 6 Conclusions -- References -- *-20pt Benchmarks and Software of Model Order Reduction -- A Non-stationary Thermal-Block Benchmark Model for Parametric Model Order Reduction -- 1 Introduction -- 2 Problem Description -- 3 Problem Variants -- 3.1 Four-Parameter LTI System -- 3.2 Single-Parameter LTI System -- 3.3 Non-parametric LTI System -- 4 Conclusion -- References -- Parametric Model Order Reduction Using pyMOR -- 1 Introduction -- 2 Software Design -- 3 Overview of Model Order Reduction Methods -- 3.1 Reduced Basis Method -- 3.2 System-Theoretic Methods -- 4 Numerical Results -- 4.1 Non-parametric Version -- 4.2 Single-Parameter Version -- 4.3 Four-Parameter Version -- 5 Conclusions -- References -- Matrix Equations, Sparse Solvers: M-M.E.S.S.-2.0.1-Philosophy, Features, and Application for (Parametric) Model Order Reduction -- 1 Introduction -- 1.1 A Brief History of M-M.E.S.S. -- 1.2 Structure of This Chapter -- 2 M-M.E.S.S.-Philosophy and Features -- 2.1 Available Solver Functions and Underlying Methods -- 3 Model Order Reduction in M-M.E.S.S. -- 3.1 IRKA and Classic Balanced Truncation -- 3.2 Further Variants of Balanced Truncation -- 4 Parametric Model Order Reduction Using M-M.E.S.S. -- 4.1 Piecewise MOR -- 4.2 Interpolation of Transfer Functions -- 5 Numerical Experiments -- References -- MORLAB-The Model Order Reduction LABoratory -- 1 Introduction -- 2 Code Design Principles -- 2.1 Toolbox Structure -- 2.2 Function Interfaces -- 2.3 Documentation -- 3 Additive System Decomposition Approach -- 3.1 Standard System Case -- 3.2 Descriptor System Case -- 4 Model Reduction with the MORLAB Toolbox -- 4.1 First-Order Methods -- 4.2 Second-Order Methods. 327 $a5 Numerical Examples. 410 0$aInternational Series of Numerical Mathematics 606 $aSystem theory$xHistory 606 $aDynamics$xStatistical methods 606 $aTeoria de sistemes$2thub 606 $aDinàmica$2thub 608 $aCongressos$2thub 608 $aLlibres electṛnics$2thub 615 0$aSystem theory$xHistory. 615 0$aDynamics$xStatistical methods. 615 7$aTeoria de sistemes 615 7$aDinàmica 676 $a309.173092 702 $aBenner$b Peter 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466393103316 996 $aModel reduction of complex dynamical systems$92860604 997 $aUNISA LEADER 06468nam 22006615 450 001 9910483766503321 005 20251113191157.0 010 $a3-319-47674-2 024 7 $a10.1007/978-3-319-47674-2 035 $a(CKB)3710000000909170 035 $a(DE-He213)978-3-319-47674-2 035 $a(MiAaPQ)EBC6280973 035 $a(MiAaPQ)EBC5586914 035 $a(Au-PeEL)EBL5586914 035 $a(OCoLC)960696038 035 $a(PPN)196323355 035 $a(EXLCZ)993710000000909170 100 $a20161009d2016 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data $e15th China National Conference, CCL 2016, and 4th International Symposium, NLP-NABD 2016, Yantai, China, October 15-16, 2016, Proceedings /$fedited by Maosong Sun, Xuanjing Huang, Hongfei Lin, Zhiyuan Liu, Yang Liu 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XVIII, 460 p. 139 illus.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v10035 300 $aIncludes index. 311 08$a3-319-47673-4 327 $aSemantics -- Improving Chinese Semantic Role Labeling with English Proposition Bank -- Transition-based Chinese Semantic Dependency Graph Parsing -- Improved Graph-based Dependency Parsing via Hierarchical LSTM Networks -- Machine Translation -- Error Analysis of English-Chinese Machine Translation -- I Can Guess What You Mean: A Monolingual Query Enhancement for Machine Translation -- Keeping the Meanings of the Source Text: An introduction to Yes Translate -- Sentence Alignment Method Based on Maximum Entropy Model Using Anchor Sentences -- Using Collaborative Training Method to build Vietnamese Dependency Treebank -- Multilinguality in NLP -- A Novel Approach to Improve the Mongolian Language Model using Intermediate Characters -- Improved Joint Kazakh POS Tagging and Chunking -- Coping with problems of Unicoded Traditional Mongolian -- Tibetan Person Attributes Extraction Based on BP Neural Network -- Semi-supervised Learning for Mongolian Morphological Segmentation -- Investigation and use of methods for defining the extends of similarity of Kazakh language sentences -- Knowledge graph and information extraction -- Recognizing Biomedical Named Entities Based on the Sentence Vector/Twin Word Embeddings Conditioned Bidirectional LSTM -- Definition Extraction with LSTM Recurrent Neural Networks -- Event Extraction via Bidirectional Long Short-Term Memory Tensor Neural Networks -- Chinese Hedge Scope Detection Based on Structure and Semantic Information -- Combining Event-level and Cross-event Semantic Information for Event-Oriented Relation Classification by SCNN -- Linguistic resource annotation and evaluation -- The Constitution of a Fine-Grained Opinion Annotated Corpus on Weibo -- The Construction of a Customized Medical Corpus for Assisting Chinese Clinicians in English Research Article Writing -- Pages Information retrieval and question answering -- Topic-Sentiment Mining from Multiple Text Collections -- A New Focus Strategy for Efficient DialogManagement -- Text classification and summarization -- Recognizing Textual Entailment via Multi-task Knowledge Assisted LSTM -- Multilingual Multi-document Summarization with Enhanced hLDA Features -- News Abridgement Algorithm Based on Word Alignment and Syntactic Parsing -- A Hierarchical LSTM Model for Joint Tasks -- Enhancing Neural Disfluency Detection with Hand-crafted Features -- Social computing and sentiment analysis -- Active Learning for Age Regression in Social Media -- A Novel Approach for Discovering Local Community Structure in Networks -- Identifying Suspected Cybermob on Tieba -- Chinese Sentiment Analysis Exploiting Heterogeneous Segmentations -- Towards Scalable Emotion Classification in Microblog Based on Noisy Training Data -- NLP Applications -- A Bootstrapping Approach to Symptom Entity Extraction on Chinese Electronic Medical Records -- Automatic Naming of Speakers in Video via Name-Face Mapping -- Image Tag Recommendation via Deep Cross-modal Correlation Mining -- Is Local Window Essential for Neural Network based Chinese Word Segmentation . 330 $aThis book constitutes the proceedings of the 15th China National Conference on Computational Linguistics, CCL 2016, and the 4th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2016, held in Yantai City, China, in October 2016. The 29 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 85 submissions. They were organized in topical sections named: semantics; machine translation; multilinguality in NLP; knowledge graph and information extraction; linguistic resource annotation and evaluation; information retrieval and question answering; text classification and summarization; social computing and sentiment analysis; and NLP applications. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v10035 606 $aNatural language processing (Computer science) 606 $aArtificial intelligence 606 $aComputer networks 606 $aNatural Language Processing (NLP) 606 $aArtificial Intelligence 606 $aComputer Communication Networks 615 0$aNatural language processing (Computer science). 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 14$aNatural Language Processing (NLP). 615 24$aArtificial Intelligence. 615 24$aComputer Communication Networks. 676 $a495.10183 702 $aSun$b Maosong$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHuang$b Xuanjing$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLin$b Hongfei$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLiu$b Zhiyuan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLiu$b Yang$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483766503321 996 $aChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data$92199626 997 $aUNINA