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Big Data and Social Computing : 9th China National Conference, BDSC 2024, Harbin, China, August 8-10, 2024, Proceedings
| Big Data and Social Computing : 9th China National Conference, BDSC 2024, Harbin, China, August 8-10, 2024, Proceedings |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (486 pages) |
| Altri autori (Persone) |
CaoZhidong
WuSuran ChenYang ZhanXiu-Xiu |
| Collana | Communications in Computer and Information Science Series |
| ISBN | 981-9758-03-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Digital Society and Public Security -- Early Warning Methods Based on a Real Time Series Dataset: A Comparative Study -- 1 Introduction -- 2 Methods -- 2.1 Traditional Models -- 2.2 Artificial Neural Network Models -- 3 Experiment -- 3.1 Sample and Preprocessing -- 3.2 Experiment Settings -- 3.3 Artificial Neural Network Methods -- 4 Results -- 5 Conclusion -- References -- EG-ConMix: An Intrusion Detection Method Based on Graph Contrastive Learning -- 1 Introduction -- 2 Related Work -- 2.1 Classical Intrusion Detection Methods -- 2.2 Self-supervised Learning -- 3 Methodology -- 3.1 Network Traffic Graphs Construction -- 3.2 Model Architecture -- 4 Experiments -- 4.1 Datasets -- 4.2 Comparison Methods -- 4.3 Experimental Settings -- 4.4 Evaluation on Intrusion Detection -- 4.5 Parametric Analysis -- 5 Conclusion -- References -- Network Analysis Reveals Regional Disparity in COVID-19 Policymaking -- 1 Introduction -- 2 Data -- 3 Methodology -- 3.1 Data Preprocessing -- 3.2 Keywords Extraction -- 3.3 Keywords Co-occurrence Matrix -- 3.4 QAP Test -- 3.5 Agenda Setting Networks Visualization -- 4 Results -- 4.1 Keywords Extraction -- 4.2 QAP Test -- 4.3 Agenda Setting Networks Visualization -- 5 Conclusion -- References -- Exploring Urban Spatial-temporal Patterns via Large-scale Vehicle Travel Data: The Role of Geographical Attributes and Traveler Characteristics -- 1 Introduction -- 2 Related Works -- 3 OD-Based Spatial-Temporal Patterns Discovering -- 3.1 Dataset -- 3.2 Tensor Decomposition Based Pattern Analysis -- 4 Influence Analysis of Geographical Attributes -- 4.1 LightGBM -- 4.2 Importance and Relationships Analysis -- 5 Analysis of Different Vehicular Travelers Groups -- 5.1 Classification of Travelers Groups -- 5.2 Patterns of Different Vehicular Travelers -- 6 Conclusion -- References.
Mapping Gridded Wealth Index Using Open Geospatial Data in Zambia -- 1 Introduction -- 2 Data and Methods -- 2.1 Study Area and Data Sources -- 2.2 Methods -- 3 Results -- 3.1 Model Performance -- 3.2 Variable Importance Analysis -- 3.3 Mapping 4 km Grid WI -- 4 Discussion -- References -- Bidirectional Multi-grain Graph Convolution Network for Origin-Destination Demand Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Origin-Destination Demand Prediction -- 2.2 Graph Convolutional Neural Network -- 3 Preliminaries -- 4 Methodology -- 4.1 BiDP Model -- 4.2 Origin-Destination Bidirectional Relevance Level -- 4.3 Multi-grain Feature Extraction -- 4.4 Global Temporal Correlation Module -- 5 Experiments -- 5.1 Datasets -- 5.2 Experiment Settings -- 5.3 Experiment Results -- 6 Conclusion -- References -- Modelling and Simulation of Social Systems -- The Prospects of Multi-modal Pre-trained Models in Epidemic Forecasting -- 1 Introduction -- 2 Challenges in Epidemic Data Collection and Processing -- 2.1 Data Lags, Missing and Inconsistencies -- 2.2 Impact of Emergencies and Non-linear Effects -- 2.3 Data Heterogeneity -- 3 Why Use Multi-modal Pre-trained Models? -- 3.1 Data Lags, Missing and Inconsistencies -- 3.2 Impact of Emergencies and Non-linear Effects -- 3.3 Data Heterogeneity -- 4 How to Model Multi-modal Information? -- 5 How to Build a Multimodal Pre-trained Model for Spatiotemporal Graph Diffusion? -- 6 What to Learn in Pre-trained? -- 7 The Advantages of Multi-modal Models -- 7.1 Enhanced Data Processing Capability -- 7.2 Enhanced Feature Learning Capability -- 7.3 Integration of Multiple Perspectives -- 8 Conclusion -- References -- Deep Reinforcement Learning Based Dynamic Bus Timetable Scheduling with Bidirectional Constraints -- 1 Introduction -- 2 Related Works -- 2.1 Traditional Bus Timetable Scheduling Methods. 2.2 Reinforcement Learning in Bus Timetable Scheduling -- 3 The Bus Timetable Scheduling Problem -- 4 Dynamic Bus Timetable Scheduling with Bidirectional Constraints Based on Deep Reinforcement Learning -- 4.1 MDP Model of Bus Timetable Scheduling Problem -- 4.2 Deep Reinforcement Learning Agent -- 5 Experimental Results -- 5.1 Real-World Dataset -- 5.2 Baseline Algorithms -- 5.3 Experimental Settings -- 5.4 Experimental Results of Offline Scheduling -- 5.5 Experimental Results of Online Scheduling -- 5.6 Analysis of Performance with Different -- 6 Conclusion -- References -- Modeling Knowledge Spillover Effects in High-Speed Rail Development: A Discrete Simulation Approach Using Cellular Automata -- 1 Introduction -- 2 Cellular Automata Model for Knowledge Spillover in High-Speed Rail Networks -- 2.1 Complexity of Inter-Entity Interactions in Knowledge Spillover Networks -- 2.2 Design of Cellular Automata Model -- 3 Data and Methods -- 3.1 The Influence of High-Speed Railway on Knowledge Spillover Rule -- 3.2 Knowledge Overflow Space Evolutionary Data and Cellular Automata Rules -- 4 Results and Discussion -- 4.1 There is No Emergence of Spatial Knowledge Spillover Effect of High-Speed Rail -- 4.2 The Emergence of Spatial Knowledge Spillover Effect of High-Speed Railway -- 4.3 Spatial Distribution Characteristics of High-Speed Rail Impacts -- 5 Conclusion -- References -- Educators' Networking Interacts with Digital Competence Heterogeneity to Enhance the Implementation of AIEd: A Mixed‐Methods Study -- 1 Introduction -- 2 Conceptual Framework -- 2.1 Data Collection -- 2.2 Data Analysis -- 2.3 Components Influencing Quality of AIEd Experience -- 3 Simulation Modeling -- 3.1 Environment -- 3.2 Agents -- 3.3 Simulation -- 3.4 Results -- 4 Discussion and Conclusions -- References. Intelligent Fatigue Driving Detection Method Based on Fusion of Smartphone and Smartwatch Data -- 1 Introduction -- 2 Road Driving Experiment Design -- 2.1 Experimental Design -- 2.2 Experimental Equipment -- 2.3 Fatigue Level Determination -- 3 Data Feature Extraction -- 4 Fatigue Driving Detection Model Based on Attention and LSTM -- 4.1 Modeling Method Based on Attention Mechanism and LSTM Neural Network -- 4.2 Fatigue Driving Behavior Detection Method Based on Normal Model -- 5 Result -- 5.1 The Results of Fatigue Detection Based on Trajectory Data -- 5.2 The Results of Fatigue Detection Based on the Fusion of Trajectory and Physiological Data -- 6 Conclusion -- References -- SCPM-R+ER: A R+ER-based Algorithm for Mining Spatial Co-location Patterns -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 4 Approach -- 4.1 Mining Framework -- 4.2 The Algorithm -- 4.3 Time Complexity Analysis -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 The Quantity of Extended Maximal Cliques -- 5.3 Efficiency Analysis -- 5.4 Memory Consumption Analysis -- 6 Conclusion -- References -- Internet Intelligent Algorithm Governance -- Extracting Spatial High Utility Co-location Patterns Based on Fuzzy Feature Clusters -- 1 Introduction -- 2 Related Work -- 3 Relevant Definitions -- 3.1 Construction of Fuzzy Spatial Neighbor Relationships -- 3.2 Calculation of Fuzzy Utility -- 4 Fuzzy Chameleon Clustering Algorithm -- 5 Thresholds Setting of FCC Algorithm -- 6 Complexity Analysis -- 7 Experimentation and Analysis -- 7.1 Experimental Environment -- 7.2 Rationality Analysis -- 7.3 Extensibility Assessment -- 7.4 Visualization Analysis -- 8 Summary and Outlook -- References -- Incremental Network Traffic Category Models Based on Hybrid Learning Strategies -- 1 Introduction -- 2 Related Work -- 2.1 Network Traffic Classification -- 2.2 Class-Incremental Learning. 3 Framework -- 3.1 Traffic Data Preprocessing Module -- 3.2 Traffic Classification Model -- 3.3 Incremental Learning Data Maintenance Module -- 3.4 Overall Framework -- 4 Experiment -- 4.1 Experimental Preparation -- 4.2 Implementation Experiments -- 5 Conclusion -- References -- Modeling the BGP Prefix Hijack via Pollution and Recovery Processes -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Events of BGP Hijack -- 3.2 Topology Map of AS -- 4 Analysis of Hijack Events -- 4.1 Path Hijack Events Distribution -- 4.2 Path Hijack in As Topology -- 5 Hijack Evaluation Modeling -- 5.1 Pollution Process Modeling -- 5.2 Announce Process Modeling -- 5.3 Hijack Evaluation Experiment -- 6 Conclusion -- References -- A Weakly Supervised Method for Encrypted Traffic Classification in the Dark Web -- 1 Introduction -- 2 Related Works -- 2.1 Content-Based Classification -- 2.2 Statistical Feature-Based Classification -- 2.3 Deep Learning-Based Classification -- 3 Overview of the Method -- 3.1 Anomalous Encrypted Traffic Identification -- 3.2 Encrypted Traffic Classification -- 4 Experiments -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Experimental Setup -- 4.4 Traffic Binary Classification Model Performance -- 4.5 Encrypted Traffic Classification Model Performance -- 5 Conclusions -- References -- Rumor Detection Based on Conflict and Bot Features -- 1 Introduction -- 2 Related Work -- 2.1 Single-Modal Rumor Detection -- 2.2 Multi-modal Rumor Detection -- 2.3 Conflict Detection -- 2.4 Bot Detection -- 3 Method -- 3.1 Problem Statement -- 3.2 Graph Construction -- 3.3 Bot Feature -- 3.4 Dual GCN Module -- 3.5 Rumor Classification Module -- 4 Experiment -- 4.1 Datasets -- 4.2 Baseline -- 4.3 Experimental Settings -- 4.4 Results -- 4.5 Ablation Study -- 4.6 Bot Feature Selection -- 4.7 Early Detection -- 5 Discussions and Conclusion -- References. Social Network and Group Behavior. |
| Record Nr. | UNINA-9910878986203321 |
Meng Xiaofeng
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big Data and Social Computing [[electronic resource] ] : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang
| Big Data and Social Computing [[electronic resource] ] : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina |
621.39
004.6 |
| Altri autori (Persone) |
ChenYang
SuoLiming XuanQi ZhangZi-Ke |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer engineering
Computer networks Computer systems Image processing—Digital techniques Computer vision Application software Computer Engineering and Networks Computer System Implementation Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications |
| ISBN | 981-9939-25-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Technology and Sustainable Development -- A Power Consumption Forecasting Method Based on Knowledge Embedding Under the Influence of the COVID-19 Pandemic -- An efficient regional co-location pattern mining algorithm over extended objects based on neighborhood distribution relation computation -- Research on Multi-objective Optimization Algorithm for Coal Blending -- Social Network and Group Behavior -- Research on the Public Value of Government Social Media Content and Communication Strategies under “Infodemic” -- Location Recommendations Based on Multi-view Learning and Attention-enhanced Graph Networks -- Driving Style Classification and Dynamic Recognition Considering Traffic State -- Who Connects Wikipedia? A Deep Analysis of Node Roles and Connection Patterns in Wikilink Network -- Digital infrastructure and the Intelligent Society -- Social Behavior-Aware Driving Intention Detection using Spatio-Temporal Attention Network -- Intelligent Government Decision-Making: A Multidimensional Policy Text Visualization Analysis System -- Heuristic Approach to Curate Disease Taxonomy Beyond Nosology-based Standards -- Root Cause Localization Method of Base Station Cells with Poor Quality using AI+SHAP -- Digital Society and Public Security Does Internet Use Promote the Garbage Classification Behavior of Farmers? -- Empirical Evidence from Rural China -- Traffic State Propagation Prediction based on SAE-LSTM-SAD under the SCATS -- Citation Prediction via Influence Representation using Temporal Graphs -- Enhancing Time Series Anomaly Detection with Graph Learning Techniques -- Image Dehazing based on CycleGAN with an Enhanced Generator and a Multiscale Discriminator -- Artificial Intelligence and Cognitive Science -- Accurate and Rapid Localization of Tea Bud Leaf Picking Point based on YOLOv8 -- Compressor Fault Diagnosis Based on Graph Attention Network -- Conductance-Threshold Dual Adaptive Spiking Neural Networks for Speech Recognition -- Mitigating Backdoor Attacks Using Prediction of Model Update Trends -- The Motor Fault Diagnosis Based On Current Signal With Graph Attention Network -- Internet Intelligent Algorithm Governance -- NILSIC-BERT4Rec: Sequential Recommendation with Non-Invasive and Interest Capturing Self-Attention Mechanism -- Rethinking the Robustness of Graph Neural Networks -- MDC: An Interpretable GNNs Method Based on Node Motif Degree and Graph Diffusion Convolution -- Missing data imputation for traffic flow data using SAE-GAN-SAD -- Scaffold Data Augmentation for Molecular Property Prediction. . |
| Record Nr. | UNISA-996546837703316 |
|
Meng Xiaofeng
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Big Data and Social Computing : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang
| Big Data and Social Computing : 8th China National Conference, BDSC 2023, Urumqi, China, July 15–17, 2023, Proceedings / / edited by Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang |
| Autore | Meng Xiaofeng |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina |
621.39
004.6 |
| Altri autori (Persone) |
ChenYang
SuoLiming XuanQi ZhangZi-Ke |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer engineering
Computer networks Computer systems Image processing—Digital techniques Computer vision Application software Computer Engineering and Networks Computer System Implementation Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications |
| ISBN | 981-9939-25-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Technology and Sustainable Development -- A Power Consumption Forecasting Method Based on Knowledge Embedding Under the Influence of the COVID-19 Pandemic -- An efficient regional co-location pattern mining algorithm over extended objects based on neighborhood distribution relation computation -- Research on Multi-objective Optimization Algorithm for Coal Blending -- Social Network and Group Behavior -- Research on the Public Value of Government Social Media Content and Communication Strategies under “Infodemic” -- Location Recommendations Based on Multi-view Learning and Attention-enhanced Graph Networks -- Driving Style Classification and Dynamic Recognition Considering Traffic State -- Who Connects Wikipedia? A Deep Analysis of Node Roles and Connection Patterns in Wikilink Network -- Digital infrastructure and the Intelligent Society -- Social Behavior-Aware Driving Intention Detection using Spatio-Temporal Attention Network -- Intelligent Government Decision-Making: A Multidimensional Policy Text Visualization Analysis System -- Heuristic Approach to Curate Disease Taxonomy Beyond Nosology-based Standards -- Root Cause Localization Method of Base Station Cells with Poor Quality using AI+SHAP -- Digital Society and Public Security Does Internet Use Promote the Garbage Classification Behavior of Farmers? -- Empirical Evidence from Rural China -- Traffic State Propagation Prediction based on SAE-LSTM-SAD under the SCATS -- Citation Prediction via Influence Representation using Temporal Graphs -- Enhancing Time Series Anomaly Detection with Graph Learning Techniques -- Image Dehazing based on CycleGAN with an Enhanced Generator and a Multiscale Discriminator -- Artificial Intelligence and Cognitive Science -- Accurate and Rapid Localization of Tea Bud Leaf Picking Point based on YOLOv8 -- Compressor Fault Diagnosis Based on Graph Attention Network -- Conductance-Threshold Dual Adaptive Spiking Neural Networks for Speech Recognition -- Mitigating Backdoor Attacks Using Prediction of Model Update Trends -- The Motor Fault Diagnosis Based On Current Signal With Graph Attention Network -- Internet Intelligent Algorithm Governance -- NILSIC-BERT4Rec: Sequential Recommendation with Non-Invasive and Interest Capturing Self-Attention Mechanism -- Rethinking the Robustness of Graph Neural Networks -- MDC: An Interpretable GNNs Method Based on Node Motif Degree and Graph Diffusion Convolution -- Missing data imputation for traffic flow data using SAE-GAN-SAD -- Scaffold Data Augmentation for Molecular Property Prediction. . |
| Record Nr. | UNINA-9910744506003321 |
|
Meng Xiaofeng
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The State of China’s State Capitalism [[electronic resource] ] : Evidence of Its Successes and Pitfalls / / edited by Juann H. Hung, Yang Chen
| The State of China’s State Capitalism [[electronic resource] ] : Evidence of Its Successes and Pitfalls / / edited by Juann H. Hung, Yang Chen |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Palgrave Macmillan, , 2018 |
| Descrizione fisica | 1 online resource (xxiii, 354 pages) |
| Disciplina | 330.951 |
| Soggetto topico |
Globalization
Asian Economics Asian Politics |
| ISBN | 981-13-0983-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Land and Debt -- 1. Fiscal Decentralization, Yardstick Competition in Determining Chinese Local Governments’ Land Conveyance Behavior -- 2. Determinants of the Urban Investment Bonds in China.-Part II Real Estate Sector -- 3. China’s Housing Price: Where Are the Bubbles? -- 4. When Wanda Plaza Comes to the Yangtze River Delta: Will the Land Prices Increase? -- Part III Energy and Environment -- 5. Forecasting the Carbon Price in China Pilot Emission Trading Scheme: A Structural Time Series Approach -- 6. The Energy Paradox: Evidence from Refrigerator Market in China.-Part IV Income Inequality -- 7. Income Inequality in China and the Role of Fiscal Policies: An Empirical Study of Chinese Provincial Data -- 8. Does Economic Inequality Matter for Nationalism? -- 9. The Rise in China’s Gender Income Inequality -- Part V Foreign Direct Investment -- 10. Inward FDI and Economic Growth: A Comparative Analysis of China Versus India -- 11. The Role of the Exchange Rate in China’s Outward Foreign Direct Investment -- Part VI Corporate Finance -- 12. Corporate Marginal Tax Rate Estimation: Evidence Based on China’s Listed Companies -- 13. The Optimal Model for Operating Cash Flow in Chinese Industries. |
| Record Nr. | UNINA-9910299643703321 |
| Singapore : , : Springer Singapore : , : Imprint : Palgrave Macmillan, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
System Simulation Techniques with MATLAB and Simulink
| System Simulation Techniques with MATLAB and Simulink |
| Autore | Xue Dingyü |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : John Wiley & Sons, Incorporated, , 2013 |
| Descrizione fisica | 1 online resource (485 pages) |
| Disciplina | 620.002 |
| Altri autori (Persone) | ChenYang |
| Soggetto topico | System analysis - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9781118694350
9781118647929 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- SYSTEM SIMULATION TECHNIQUES WITH MATLAB® AND SIMULINK® -- Contents -- Foreword -- Preface -- 1 Introduction to System Simulation Techniques and Applications -- 1.1 Overview of System Simulation Techniques -- 1.2 Development of Simulation Software -- 1.2.1 Development of Earlier Mathematics Packages -- 1.2.2 Development of Simulation Software and Languages -- 1.3 Introduction to MATLAB -- 1.3.1 Brief History of the Development of MATLAB -- 1.3.2 Characteristics of MATLAB -- 1.4 Structure of the Book -- 1.4.1 Structure of the Book -- 1.4.2 Code Download and Internet Resources -- 1.4.3 Fonts Used in this Book -- Exercises -- References -- 2 Fundamentals of MATLAB Programming -- 2.1 MATLAB Environment -- 2.1.1 MATLAB Interface -- 2.1.2 MATLAB On-line Help and Documentation -- 2.2 Data Types in MATLAB -- 2.2.1 Constants and Variables -- 2.2.2 Structure of MATLAB Statements -- 2.2.3 Matrix Representation in MATLAB -- 2.2.4 Multi-dimensional Arrays -- 2.3 Matrix Computations in MATLAB -- 2.3.1 Algebraic Computation -- 2.3.2 Logical Operations -- 2.3.3 Comparisons and Relationships -- 2.3.4 Data Type Conversion -- 2.4 Flow Structures -- 2.4.1 Loop Structures -- 2.4.2 Conditional Structures -- 2.4.3 Switches -- 2.4.4 Trial Structure -- 2.5 Programming and Tactics of MATLAB Functions -- 2.5.1 Structures of MATLAB Functions -- 2.5.2 Handling Variable Numbers of Arguments -- 2.5.3 Debugging of MATLAB Functions -- 2.5.4 Pseudo Codes -- 2.6 Two-dimensional Graphics in MATLAB -- 2.6.1 Basic Two-dimensional Graphics -- 2.6.2 Plotting Functions with Other Options -- 2.6.3 Labeling MATLAB Graphics -- 2.6.4 Adding Texts and Other Objects to Plots -- 2.6.5 Other Graphics Functions with Applications -- 2.6.6 Plotting Implicit Functions -- 2.7 Three-dimensional Graphics -- 2.7.1 Three-dimensional Curves -- 2.7.2 Surface Plots.
2.7.3 Local Processing of Graphics -- 2.8 Graphical User Interface Design in MATLAB -- 2.8.1 Graphical User Interface Tool - Guide -- 2.8.2 Handle Graphics and Properties of Objects -- 2.8.3 Menu System Design -- 2.8.4 Illustrative Examples in GUI Design -- 2.8.5 Toolbar Design -- 2.8.6 Embedding ActiveX Components in GUIs -- 2.9 Accelerating MATLAB Functions -- 2.9.1 Execution Time and Profiles of MATLAB Functions -- 2.9.2 Suggestions for Accelerating MATLAB Functions -- 2.9.3 Mex Interface Design -- Exercises -- References -- 3 MATLAB Applications in Scientific Computations -- 3.1 Analytical and Numerical Solutions -- 3.2 Solutions to Linear Algebra Problems -- 3.2.1 Inputting Special Matrices -- 3.2.2 Matrix Analysis and Computation -- 3.2.3 Inverse and Pseudo Inverse of Matrices -- 3.2.4 Similarity Transform and Decomposition of Matrices -- 3.2.5 Eigenvalues and Eigenvectors of Matrices -- 3.2.6 Solution of Matrix Equations -- 3.2.7 Nonlinear Matrix Functions -- 3.3 Solutions of Calculus Problems -- 3.3.1 Analytical Solutions to Calculus Problems -- 3.3.2 Numerical Difference and Differentiation -- 3.3.3 Numerical Integration -- 3.3.4 Numerical Multiple Integration -- 3.4 Solutions of Ordinary Differential Equations -- 3.4.1 Numerical Methods of Ordinary Differential Equations -- 3.4.2 MATLAB Solutions to ODE Problems -- 3.4.3 Conversion of ODE Sets -- 3.4.4 Validation of Numerical ODE Solutions -- 3.4.5 Solutions to Differential Algebraic Equations -- 3.4.6 Solutions to Linear Stochastic Differential Equations -- 3.4.7 Analytical Solutions to ODEs -- 3.4.8 Numerical Laplace Transforms in ODE Solutions -- 3.5 Nonlinear Equation Solutions and Optimization -- 3.5.1 Solutions of Nonlinear Equations -- 3.5.2 Solutions to Nonlinear Equations with Multiple Solutions -- 3.5.3 Unconstrained Optimization -- 3.5.4 Linear Programming. 3.5.5 Quadratic Programming -- 3.5.6 General Nonlinear Programming -- 3.5.7 Global Search Methods in Optimization Problems -- 3.6 Dynamic Programming and its Applications in Path Planning -- 3.6.1 Matrix Representation of Graphs -- 3.6.2 Optimal Path Planning of Oriented Graphs -- 3.6.3 Optimal Path Planning of Graphs -- 3.7 Data Interpolation and Statistical Analysis -- 3.7.1 Interpolation of One-dimensional Data -- 3.7.2 Interpolation of Two-dimensional Data -- 3.7.3 Least Squares Curve Fitting -- 3.7.4 Data Sorting -- 3.7.5 Fast Fourier Transform -- 3.7.6 Data Analysis and Statistics -- Exercises -- References -- 4 Mathematical Modeling and Simulation with Simulink -- 4.1 Brief Description of the Simulink Block Library -- 4.1.1 Signal Sources -- 4.1.2 Continuous Blocks -- 4.1.3 Discrete-time Blocks -- 4.1.4 Lookup Table Blocks -- 4.1.5 User-defined Functions -- 4.1.6 Math Blocks -- 4.1.7 Logic and Bit Operation Blocks -- 4.1.8 Nonlinearity Blocks -- 4.1.9 Output Blocks -- 4.1.10 Signal Related Blocks -- 4.1.11 Ports and Subsystem Blocks -- 4.1.12 Commonly Used Blocks -- 4.1.13 Other Toolboxes and Blocksets -- 4.2 Simulink Modeling -- 4.2.1 Establishing a Model Window -- 4.2.2 Connecting and Simple Manipulation of Blocks -- 4.2.3 Parameter Modification in Blocks -- 4.3 Model Manipulation and Simulation Analysis -- 4.3.1 Model Creation and Fundamental Modeling Skills -- 4.3.2 Model Explorer -- 4.3.3 On-line Help System in Simulink -- 4.3.4 Output and Printing of Simulink Models -- 4.3.5 Simulink Environment Setting -- 4.3.6 Debugging Tools of Simulink Models -- 4.4 Illustrative Examples of Simulink Modeling -- 4.5 Modeling, Simulation and Analysis of Linear Systems -- 4.5.1 Modeling of Linear Systems -- 4.5.2 Analysis Interface for Linear Systems -- 4.6 Simulation of Continuous Nonlinear Stochastic Systems. 4.6.1 Simulation of Random Signals in Simulink -- 4.6.2 Statistical Analysis of Simulation Results -- Exercises -- References -- 5 Commonly Used Blocks and Intermediate-level Modeling Skills -- 5.1 Commonly Used Blocks and Modeling Skills -- 5.1.1 Examples of Vectorized Blocks -- 5.1.2 Signals Labeling in Simulink Models -- 5.1.3 Algebraic Loop and its Elimination in Simulink Models -- 5.1.4 Zero-crossing Detection and Simulation of Simulink Models -- 5.2 Modeling and Simulation of Multivariable Linear Systems -- 5.2.1 Modeling State Space Multivariable Systems -- 5.2.2 Multivariable System Modeling with Control System Toolbox -- 5.3 Nonlinear Components with Lookup Table Blocks -- 5.3.1 Single-valued Nonlinearities -- 5.3.2 Multi-valued Nonlinearities with Memories -- 5.3.3 Multi-dimensional Lookup Table Blocks -- 5.3.4 Code Realization of Static Nonlinearities -- 5.4 Block Diagram Based Solutions of Differential Equations -- 5.4.1 Ordinary Differential Equations -- 5.4.2 Differential Algebraic Equations -- 5.4.3 Delayed Differential Equations -- 5.4.4 Switching Differential Equations -- 5.4.5 Fractional-order Differential Equations -- 5.5 Output Block Library -- 5.5.1 Output Block Group -- 5.5.2 Examples of Output Blocks -- 5.5.3 Model Parameter Display and Model Browser -- 5.5.4 Gauge Display of Signals -- 5.5.5 Digital Signal Processing Outputs -- 5.6 Three-dimensional Animation of Simulation Results -- 5.6.1 Fundamentals of Virtual Reality -- 5.6.2 V-realm Software and World Modeling -- 5.6.3 Browsing Virtual Reality World with MATLAB -- 5.6.4 Virtual Reality World Driven by Simulink Models -- 5.7 Subsystems and Block Masking Techniques -- 5.7.1 Building Subsystems -- 5.7.2 Conditional Subsystems -- 5.7.3 Masking Subsystems -- 5.7.4 Constructing Users' Own Block Library -- 5.7.5 An Illustrative Example: F-14 Aircraft Simulation -- Exercises. References -- 6 Advanced Techniques in Simulink Modeling and Applications -- 6.1 Command-line Modeling in Simulink -- 6.1.1 Simulink Models and File Manipulations -- 6.1.2 Simulink Models and Model Files -- 6.1.3 Drawing Block Diagrams with MATLAB Commands -- 6.2 System Simulation and Linearization -- 6.2.1 Execution of Simulation Process -- 6.2.2 Linearization of Nonlinear Systems -- 6.2.3 Padé Approximation to Pure Time Delays -- 6.3 S-function Programming and Applications -- 6.3.1 Writing S-functions in MATLAB -- 6.3.2 Application Example of S-functions: Simulation of ADRC Systems -- 6.3.3 Level-2 S-function Programming -- 6.3.4 Writing S-functions in C -- 6.3.5 Masking an S-function Block -- 6.4 Examples of Optimization in Simulation: Optimal Controller Design Applications -- 6.4.1 Optimal Criterion Selection for Servo Control Systems -- 6.4.2 Objective Function Creation and Optimal Controller Design -- 6.4.3 Global Optimization Approach -- Exercises -- References -- 7 Modeling and Simulation of Engineering Systems -- 7.1 Physical System Modeling with Simscape -- 7.1.1 Limitations of Conventional Modeling Methodology -- 7.1.2 Introduction to Simscape -- 7.1.3 Overview of Simscape Foundation Library -- 7.1.4 Conversions of Two Types of Signals -- 7.1.5 Brief Description of the Simscape Language -- 7.1.6 Modeling and Simulation of Complicated Electrical Network -- 7.2 Description of SimPowerSystems -- 7.3 Modeling and Simulation of Electronic Systems -- 7.3.1 Introduction to the SimElectronics Blockset -- 7.3.2 Modeling of Analogue Electronic Circuits -- 7.3.3 Modeling of Digital Electronic Circuits -- 7.3.4 Modeling of Power Electronics Circuits -- 7.3.5 Embedding Spice Models in Simulink -- 7.4 Simulation of Motors and Electric Drive Systems -- 7.4.1 Simulation of DC Motor Drive Systems -- 7.4.2 Simulation of AC Motor Drive Systems. 7.5 Modeling and Simulation of Mechanical Systems. |
| Record Nr. | UNINA-9910795815203321 |
|
Xue Dingyü
|
||
| New York : , : John Wiley & Sons, Incorporated, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
System Simulation Techniques with MATLAB and Simulink
| System Simulation Techniques with MATLAB and Simulink |
| Autore | Xue Dingyü |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : John Wiley & Sons, Incorporated, , 2013 |
| Descrizione fisica | 1 online resource (485 pages) |
| Disciplina | 620.002 |
| Altri autori (Persone) | ChenYang |
| Soggetto topico | System analysis - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9781118694350
9781118647929 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- SYSTEM SIMULATION TECHNIQUES WITH MATLAB® AND SIMULINK® -- Contents -- Foreword -- Preface -- 1 Introduction to System Simulation Techniques and Applications -- 1.1 Overview of System Simulation Techniques -- 1.2 Development of Simulation Software -- 1.2.1 Development of Earlier Mathematics Packages -- 1.2.2 Development of Simulation Software and Languages -- 1.3 Introduction to MATLAB -- 1.3.1 Brief History of the Development of MATLAB -- 1.3.2 Characteristics of MATLAB -- 1.4 Structure of the Book -- 1.4.1 Structure of the Book -- 1.4.2 Code Download and Internet Resources -- 1.4.3 Fonts Used in this Book -- Exercises -- References -- 2 Fundamentals of MATLAB Programming -- 2.1 MATLAB Environment -- 2.1.1 MATLAB Interface -- 2.1.2 MATLAB On-line Help and Documentation -- 2.2 Data Types in MATLAB -- 2.2.1 Constants and Variables -- 2.2.2 Structure of MATLAB Statements -- 2.2.3 Matrix Representation in MATLAB -- 2.2.4 Multi-dimensional Arrays -- 2.3 Matrix Computations in MATLAB -- 2.3.1 Algebraic Computation -- 2.3.2 Logical Operations -- 2.3.3 Comparisons and Relationships -- 2.3.4 Data Type Conversion -- 2.4 Flow Structures -- 2.4.1 Loop Structures -- 2.4.2 Conditional Structures -- 2.4.3 Switches -- 2.4.4 Trial Structure -- 2.5 Programming and Tactics of MATLAB Functions -- 2.5.1 Structures of MATLAB Functions -- 2.5.2 Handling Variable Numbers of Arguments -- 2.5.3 Debugging of MATLAB Functions -- 2.5.4 Pseudo Codes -- 2.6 Two-dimensional Graphics in MATLAB -- 2.6.1 Basic Two-dimensional Graphics -- 2.6.2 Plotting Functions with Other Options -- 2.6.3 Labeling MATLAB Graphics -- 2.6.4 Adding Texts and Other Objects to Plots -- 2.6.5 Other Graphics Functions with Applications -- 2.6.6 Plotting Implicit Functions -- 2.7 Three-dimensional Graphics -- 2.7.1 Three-dimensional Curves -- 2.7.2 Surface Plots.
2.7.3 Local Processing of Graphics -- 2.8 Graphical User Interface Design in MATLAB -- 2.8.1 Graphical User Interface Tool - Guide -- 2.8.2 Handle Graphics and Properties of Objects -- 2.8.3 Menu System Design -- 2.8.4 Illustrative Examples in GUI Design -- 2.8.5 Toolbar Design -- 2.8.6 Embedding ActiveX Components in GUIs -- 2.9 Accelerating MATLAB Functions -- 2.9.1 Execution Time and Profiles of MATLAB Functions -- 2.9.2 Suggestions for Accelerating MATLAB Functions -- 2.9.3 Mex Interface Design -- Exercises -- References -- 3 MATLAB Applications in Scientific Computations -- 3.1 Analytical and Numerical Solutions -- 3.2 Solutions to Linear Algebra Problems -- 3.2.1 Inputting Special Matrices -- 3.2.2 Matrix Analysis and Computation -- 3.2.3 Inverse and Pseudo Inverse of Matrices -- 3.2.4 Similarity Transform and Decomposition of Matrices -- 3.2.5 Eigenvalues and Eigenvectors of Matrices -- 3.2.6 Solution of Matrix Equations -- 3.2.7 Nonlinear Matrix Functions -- 3.3 Solutions of Calculus Problems -- 3.3.1 Analytical Solutions to Calculus Problems -- 3.3.2 Numerical Difference and Differentiation -- 3.3.3 Numerical Integration -- 3.3.4 Numerical Multiple Integration -- 3.4 Solutions of Ordinary Differential Equations -- 3.4.1 Numerical Methods of Ordinary Differential Equations -- 3.4.2 MATLAB Solutions to ODE Problems -- 3.4.3 Conversion of ODE Sets -- 3.4.4 Validation of Numerical ODE Solutions -- 3.4.5 Solutions to Differential Algebraic Equations -- 3.4.6 Solutions to Linear Stochastic Differential Equations -- 3.4.7 Analytical Solutions to ODEs -- 3.4.8 Numerical Laplace Transforms in ODE Solutions -- 3.5 Nonlinear Equation Solutions and Optimization -- 3.5.1 Solutions of Nonlinear Equations -- 3.5.2 Solutions to Nonlinear Equations with Multiple Solutions -- 3.5.3 Unconstrained Optimization -- 3.5.4 Linear Programming. 3.5.5 Quadratic Programming -- 3.5.6 General Nonlinear Programming -- 3.5.7 Global Search Methods in Optimization Problems -- 3.6 Dynamic Programming and its Applications in Path Planning -- 3.6.1 Matrix Representation of Graphs -- 3.6.2 Optimal Path Planning of Oriented Graphs -- 3.6.3 Optimal Path Planning of Graphs -- 3.7 Data Interpolation and Statistical Analysis -- 3.7.1 Interpolation of One-dimensional Data -- 3.7.2 Interpolation of Two-dimensional Data -- 3.7.3 Least Squares Curve Fitting -- 3.7.4 Data Sorting -- 3.7.5 Fast Fourier Transform -- 3.7.6 Data Analysis and Statistics -- Exercises -- References -- 4 Mathematical Modeling and Simulation with Simulink -- 4.1 Brief Description of the Simulink Block Library -- 4.1.1 Signal Sources -- 4.1.2 Continuous Blocks -- 4.1.3 Discrete-time Blocks -- 4.1.4 Lookup Table Blocks -- 4.1.5 User-defined Functions -- 4.1.6 Math Blocks -- 4.1.7 Logic and Bit Operation Blocks -- 4.1.8 Nonlinearity Blocks -- 4.1.9 Output Blocks -- 4.1.10 Signal Related Blocks -- 4.1.11 Ports and Subsystem Blocks -- 4.1.12 Commonly Used Blocks -- 4.1.13 Other Toolboxes and Blocksets -- 4.2 Simulink Modeling -- 4.2.1 Establishing a Model Window -- 4.2.2 Connecting and Simple Manipulation of Blocks -- 4.2.3 Parameter Modification in Blocks -- 4.3 Model Manipulation and Simulation Analysis -- 4.3.1 Model Creation and Fundamental Modeling Skills -- 4.3.2 Model Explorer -- 4.3.3 On-line Help System in Simulink -- 4.3.4 Output and Printing of Simulink Models -- 4.3.5 Simulink Environment Setting -- 4.3.6 Debugging Tools of Simulink Models -- 4.4 Illustrative Examples of Simulink Modeling -- 4.5 Modeling, Simulation and Analysis of Linear Systems -- 4.5.1 Modeling of Linear Systems -- 4.5.2 Analysis Interface for Linear Systems -- 4.6 Simulation of Continuous Nonlinear Stochastic Systems. 4.6.1 Simulation of Random Signals in Simulink -- 4.6.2 Statistical Analysis of Simulation Results -- Exercises -- References -- 5 Commonly Used Blocks and Intermediate-level Modeling Skills -- 5.1 Commonly Used Blocks and Modeling Skills -- 5.1.1 Examples of Vectorized Blocks -- 5.1.2 Signals Labeling in Simulink Models -- 5.1.3 Algebraic Loop and its Elimination in Simulink Models -- 5.1.4 Zero-crossing Detection and Simulation of Simulink Models -- 5.2 Modeling and Simulation of Multivariable Linear Systems -- 5.2.1 Modeling State Space Multivariable Systems -- 5.2.2 Multivariable System Modeling with Control System Toolbox -- 5.3 Nonlinear Components with Lookup Table Blocks -- 5.3.1 Single-valued Nonlinearities -- 5.3.2 Multi-valued Nonlinearities with Memories -- 5.3.3 Multi-dimensional Lookup Table Blocks -- 5.3.4 Code Realization of Static Nonlinearities -- 5.4 Block Diagram Based Solutions of Differential Equations -- 5.4.1 Ordinary Differential Equations -- 5.4.2 Differential Algebraic Equations -- 5.4.3 Delayed Differential Equations -- 5.4.4 Switching Differential Equations -- 5.4.5 Fractional-order Differential Equations -- 5.5 Output Block Library -- 5.5.1 Output Block Group -- 5.5.2 Examples of Output Blocks -- 5.5.3 Model Parameter Display and Model Browser -- 5.5.4 Gauge Display of Signals -- 5.5.5 Digital Signal Processing Outputs -- 5.6 Three-dimensional Animation of Simulation Results -- 5.6.1 Fundamentals of Virtual Reality -- 5.6.2 V-realm Software and World Modeling -- 5.6.3 Browsing Virtual Reality World with MATLAB -- 5.6.4 Virtual Reality World Driven by Simulink Models -- 5.7 Subsystems and Block Masking Techniques -- 5.7.1 Building Subsystems -- 5.7.2 Conditional Subsystems -- 5.7.3 Masking Subsystems -- 5.7.4 Constructing Users' Own Block Library -- 5.7.5 An Illustrative Example: F-14 Aircraft Simulation -- Exercises. References -- 6 Advanced Techniques in Simulink Modeling and Applications -- 6.1 Command-line Modeling in Simulink -- 6.1.1 Simulink Models and File Manipulations -- 6.1.2 Simulink Models and Model Files -- 6.1.3 Drawing Block Diagrams with MATLAB Commands -- 6.2 System Simulation and Linearization -- 6.2.1 Execution of Simulation Process -- 6.2.2 Linearization of Nonlinear Systems -- 6.2.3 Padé Approximation to Pure Time Delays -- 6.3 S-function Programming and Applications -- 6.3.1 Writing S-functions in MATLAB -- 6.3.2 Application Example of S-functions: Simulation of ADRC Systems -- 6.3.3 Level-2 S-function Programming -- 6.3.4 Writing S-functions in C -- 6.3.5 Masking an S-function Block -- 6.4 Examples of Optimization in Simulation: Optimal Controller Design Applications -- 6.4.1 Optimal Criterion Selection for Servo Control Systems -- 6.4.2 Objective Function Creation and Optimal Controller Design -- 6.4.3 Global Optimization Approach -- Exercises -- References -- 7 Modeling and Simulation of Engineering Systems -- 7.1 Physical System Modeling with Simscape -- 7.1.1 Limitations of Conventional Modeling Methodology -- 7.1.2 Introduction to Simscape -- 7.1.3 Overview of Simscape Foundation Library -- 7.1.4 Conversions of Two Types of Signals -- 7.1.5 Brief Description of the Simscape Language -- 7.1.6 Modeling and Simulation of Complicated Electrical Network -- 7.2 Description of SimPowerSystems -- 7.3 Modeling and Simulation of Electronic Systems -- 7.3.1 Introduction to the SimElectronics Blockset -- 7.3.2 Modeling of Analogue Electronic Circuits -- 7.3.3 Modeling of Digital Electronic Circuits -- 7.3.4 Modeling of Power Electronics Circuits -- 7.3.5 Embedding Spice Models in Simulink -- 7.4 Simulation of Motors and Electric Drive Systems -- 7.4.1 Simulation of DC Motor Drive Systems -- 7.4.2 Simulation of AC Motor Drive Systems. 7.5 Modeling and Simulation of Mechanical Systems. |
| Record Nr. | UNINA-9910822285403321 |
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| New York : , : John Wiley & Sons, Incorporated, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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