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Advances in Variable Structure Systems and Sliding Mode Control—Theory and Applications / / edited by Shihua Li, Xinghuo Yu, Leonid Fridman, Zhihong Man, Xiangyu Wang
| Advances in Variable Structure Systems and Sliding Mode Control—Theory and Applications / / edited by Shihua Li, Xinghuo Yu, Leonid Fridman, Zhihong Man, Xiangyu Wang |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (414 pages) : illustrations |
| Disciplina | 511.326 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Control engineering
System theory Control and Systems Theory Systems Theory, Control |
| ISBN | 3-319-62896-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Lyapunov-Based Design of Homogeneous High-Order Sliding Modes.- Robustness of Homogeneous and Homogeneizable Differential Inclusions.- Practical Stability Phase and Gain Margins Concept -- Indirect Adaptive Sliding-Mode Control Using the Certainty-Equivalence Principle.- Discrete Event-Triggered Sliding Mode Control -- Speed Control of Induction Motor Servo Drives Using Terminal Sliding-Mode Controller.- Sliding Modes Control in Vehicle Longitudinal Dynamics Control -- Sliding Mode Control of Power Converters with Switching Frequency Regulation. |
| Record Nr. | UNINA-9910299881803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI 2004 : advances in artificial intelligence : 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004 : proceedings / / Geoffrey I. Webb, Xinghuo Yu (eds.)
| AI 2004 : advances in artificial intelligence : 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004 : proceedings / / Geoffrey I. Webb, Xinghuo Yu (eds.) |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin, : Springer, c2004 |
| Descrizione fisica | 1 online resource (XXII, 1272 p.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
WebbGeoffrey I
YuXing Huo |
| Collana | Lecture notes in computer science,Lecture notes in artificial intelligence |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-540-30549-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Artificial intelligence 2004 |
| Record Nr. | UNINA-9910483045003321 |
| Berlin, : Springer, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI 2021, advances in artificial intelligence : 34th Australasian Joint Conference, AI 2021, Sydney, NSW, Australia, February 2-4 2022, proceedings / / edited by Guodong Long, Xinghuo Yu, and Sen Wang
| AI 2021, advances in artificial intelligence : 34th Australasian Joint Conference, AI 2021, Sydney, NSW, Australia, February 2-4 2022, proceedings / / edited by Guodong Long, Xinghuo Yu, and Sen Wang |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (810 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-97546-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Ethical AI -- An Explanation Module for Deep Neural Networks Facing Multivariate Time Series Classification -- 1 Introduction -- 2 Related Work -- 2.1 Multivariate Time Series Classification -- 2.2 Explanation Methods -- 3 Our Approach -- 4 Experiments -- 4.1 Datasets -- 4.2 Baseline Methods -- 4.3 Evaluation Procedure -- 4.4 Results -- 5 Conclusion and Future Work -- References -- Privacy-Preserving in Double Deep-Q-Network with Differential Privacy in Continuous Spaces -- 1 Introduction -- 2 Preliminaries -- 2.1 Double Deep Q Network -- 2.2 Differential Privacy -- 3 Differentially Private Double Deep Q Network -- 3.1 Overview of Our Method -- 3.2 The Algorithm Design -- 3.3 Rationale of Using DPSGD -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Result and Analysis -- 5 Conclusion -- References -- HESIP: A Hybrid System for Explaining Sub-symbolic Predictions -- 1 Introduction -- 2 The LIME-Aleph System -- 3 The HESIP System Architecture -- 4 Ontology for HESIP -- 5 Image Information Extraction -- 6 Learning Rules in cplint -- 7 Applying HESIP to a New Problem Domain -- 8 Generating Explanations -- 9 Experiments -- 10 Comparison -- 11 Conclusion -- References -- An Explainable Recommendation Based on Acyclic Paths in an Edge-Colored Graph -- 1 Introduction -- 2 Preliminary -- 3 Proposed Method -- 3.1 Graph Construction -- 3.2 Acyclic-Path-Based Recommendation -- 3.3 Explanation by Color Sequences -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Knowledge Transfer for Deep Reinforcement Agents in General Game Playing -- 1 Introduction -- 2 Background -- 3 Transfer Learning in Deep RL General Game-Playing Agents -- 3.1 Simple Network Transfer in General Game Playing -- 3.2 Complex Network Transfer -- 3.3 Multitask Training for General Game Playing.
4 Experimental Evaluation -- 4.1 Generic Agent Designs -- 4.2 Game Variations -- 4.3 Evaluation Methodology -- 5 Results and Discussion -- 5.1 Single Network Agents -- 5.2 Complex Network Transfer -- 5.3 Multi-network Agents -- 6 Conclusion and Future Work -- References -- GSMI: A Gradient Sign Optimization Based Model Inversion Method -- 1 Introduction -- 2 Gradient Sign Model Inversion -- 2.1 Threat model -- 2.2 Overview of the Attack -- 2.3 Proposed Model Inversion: GSMI -- 2.4 Two-Pass Components Selection -- 3 Performance Evaluation -- 3.1 Experimental Setup -- 3.2 Results -- 3.3 Discussion -- 4 Related Work -- 5 Summary and Future Work -- References -- Multicollinearity Correction and Combined Feature Effect in Shapley Values -- 1 Introduction -- 2 Proposed Method -- 2.1 MCC Shapley Values for Individual Features -- 2.2 MCC Shapley Values for Combination of Two or More Features -- 2.3 Algorithm of MCC Shapley Value Calculation -- 3 Results -- 3.1 Dataset - House Prices -- 4 Conclusion -- References -- Does a Face Mask Protect My Privacy?: Deep Learning to Predict Protected Attributes from Masked Face Images -- 1 Introduction -- 2 Related Work -- 2.1 Biometrics and Privacy -- 2.2 Face Biometric and Masks -- 2.3 User Perception -- 3 Methodology -- 3.1 User Perception Survey -- 3.2 Dataset and Synthetic Mask Generation -- 3.3 Computer Vision Workflow -- 3.4 Privacy Vulnerability Index(PVI) -- 4 Evaluation Results -- 4.1 User Perception Study -- 4.2 Prediction Accuracy -- 4.3 Impact of Image Attributes -- 4.4 Privacy Invasiveness -- 5 Discussion and Conclusion -- 5.1 Predicting Protected Attributes -- 5.2 Biases from Image Attributes -- 5.3 Privacy Preservation -- 5.4 Limitations -- 5.5 Conclusion and Future Work -- References -- Representation-Induced Algorithmic Bias -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References. Contextual Importance and Utility: A Theoretical Foundation -- 1 Introduction -- 2 Theory -- 2.1 Additive Feature Attribution Methods -- 2.2 Decision Theory and Multi-attribute Utility Theory -- 2.3 Contextual Importance and Utility (CIU) -- 2.4 Contextual Influence -- 2.5 CIU Versus Additive Feature Attribution Methods -- 3 Experimental Evaluation -- 4 Conclusion -- References -- Deeper Insights into Neural Nets with Random Weights -- 1 Introduction -- 2 Literature Review on Polynomial Approximations of Activation Functions -- 3 Analysis -- 4 Simulations -- 5 Conclusions -- References -- Applications -- De Novo Molecular Generation with Stacked Adversarial Model -- 1 Introduction -- 2 Related Works -- 2.1 Generative Adversarial Models -- 2.2 Generative Models for Drug Discovery -- 3 Stacked Bidirectional Adversarial Autoencoder -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Experimental Setup -- 4.3 Experimental Evaluations -- 5 Conclusion -- References -- Tailoring Contact Based Scoring Functions for Protein Structure Prediction -- 1 Introduction -- 2 Preliminaries -- 3 Scoring Functions -- 3.1 Existing Scoring Functions -- 3.2 Proposed Scoring Functions -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Comparison of Scoring Functions -- 4.3 Comparison with Existing Methods -- 5 Conclusions -- References -- Evaluation of Deep Learning Techniques on a Novel Hierarchical Surgical Tool Dataset -- 1 Introduction -- 2 Class Hierarchies and Training Strategies -- 3 Methodology -- 3.1 Surgery Dataset -- 3.2 Surgery Hierarchy -- 3.3 CNN Training Strategies -- 3.4 Metrics Reported -- 4 Experiments and Results -- 4.1 Does Size Matter? -- 4.2 Class Frequencies -- 5 Conclusions and Future Work -- References -- Feature Extraction Using Wavelet Scattering Transform Coefficients for EMG Pattern Classification -- 1 Introduction. 2 Wavelet Scattering Transform -- 3 Data Acquisition -- 4 Results -- 4.1 Results of BioPatrec-Database -- 4.2 Results of Force-Database -- 4.3 Results of 3DC-Database -- 5 Conclusion -- References -- Modelling Eye-Gaze Movement Using Gaussian Auto-regression Hidden Markov -- 1 Introduction -- 2 Preliminaries -- 2.1 Preparation for Data Collection -- 2.2 Data Collection -- 2.3 Data Pre-processing -- 3 Methodology of Eye Gaze Predictive Modelling -- 3.1 Image Transform -- 3.2 Gaussian Auto-regression Hidden Markov -- 4 Results and Analysis -- 4.1 Eye Gaze Inducted Dynamic Changes -- 4.2 Prediction Performance -- 4.3 Training and Test -- 4.4 Accuracy Analysis -- 5 Conclusion -- References -- Strategies Improve Social Welfare: An Empirical Study of Strategic Voting in Social Networks -- 1 Introduction -- 1.1 Related Work -- 2 Model -- 2.1 Basic Notations and Definitions -- 2.2 Decision Models from the Literature -- 2.3 AU Revised Model -- 2.4 The Iterative Voting Process -- 3 Experiments -- 3.1 Experiment Settings -- 3.2 Results -- 4 Conclusion -- References -- A Network-Based Rating Mechanism Against False-Name Attack -- 1 Introduction -- 2 The Model -- 3 Weighted Rating Mechanism -- 4 Conclusion -- References -- Modular Construction Planning Using Graph Neural Network Heuristic Search -- 1 Introduction -- 2 Related work -- 2.1 Neural Search Based Planning -- 2.2 Graph Generation with Neural Networks -- 3 Problem Formulation -- 4 Approach -- 4.1 Search as Planning and Design -- 4.2 Consistency of the Training Heuristic -- 5 Data Generation and Training -- 5.1 Data Augmentation with Adjacent States -- 5.2 Training -- 6 Performance Evaluation -- 6.1 Ablation Evaluation for Synthetic Data Augmentation -- 7 Conclusions -- References -- Priority-Based Traffic Management Protocols for Autonomous Vehicles on Road Networks -- 1 Introduction. 2 Road Network Modelling -- 3 Priority-Based Traffic Management Protocols -- 3.1 Static Priority Management Protocol -- 3.2 Dynamic Priority Management Protocol -- 3.3 Vehicle-Based Priority Management Protocol -- 4 Experimental Setting and Results -- 4.1 Average Delay for the Static-Priority Management Protocol -- 4.2 Bullwhip Effect for the Static Priority Management Protocol -- 4.3 Average Delay for Different Management Protocols -- 4.4 Latency Function -- 5 Related Work and Conclusion -- References -- Improving Traffic Load Prediction with Multi-modality -- 1 Introduction -- 2 Proposed Method -- 2.1 Mathematical Formulation -- 2.2 Multi-modal Method -- 3 Data Collection and Pre-processing -- 3.1 Multi-modal Data -- 3.2 Traffic Data -- 3.3 Experiment -- 4 Discussion -- 5 Related Works -- 6 Conclusion and Future Works -- References -- Predicting Geological Material Types Using Ground Penetrating Radar -- 1 Introduction -- 2 Background -- 2.1 Site Geology -- 2.2 Interaction of Site Materials and GPR -- 2.3 Machine Learning and Feature Extraction -- 3 Gaussian Ridge Extraction -- 4 Methodology -- 4.1 Signal Segmentation and Classification Process -- 4.2 Feature Extraction Processes -- 4.3 Training and Testing of Machine Learning Models -- 5 Results and Discussion -- 5.1 Individual Feature Extraction Analysis -- 5.2 Concatenation of Features into Combined Feature Space -- 5.3 Application of Feature Selection and Majority Voting -- 6 Conclusions and Future Works -- References -- A Gated Recurrent Neural Network for Electric Vehicle Detection with Imbalanced Samples -- 1 Introduction -- 2 Imbalanced Data Processing -- 2.1 Dynamic Time Warping -- 2.2 DTW Constraints -- 3 Gated Recurrent Units Network -- 4 Empirical Study -- 4.1 Data Preparation -- 4.2 The GRU Network Trianing and Validation -- 5 Conclusion -- References. User-Defined Smart Contracts Using Answer Set Programming. |
| Record Nr. | UNINA-9910552712103321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI 2021, advances in artificial intelligence : 34th Australasian Joint Conference, AI 2021, Sydney, NSW, Australia, February 2-4 2022, proceedings / / edited by Guodong Long, Xinghuo Yu, and Sen Wang
| AI 2021, advances in artificial intelligence : 34th Australasian Joint Conference, AI 2021, Sydney, NSW, Australia, February 2-4 2022, proceedings / / edited by Guodong Long, Xinghuo Yu, and Sen Wang |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (810 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-97546-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Ethical AI -- An Explanation Module for Deep Neural Networks Facing Multivariate Time Series Classification -- 1 Introduction -- 2 Related Work -- 2.1 Multivariate Time Series Classification -- 2.2 Explanation Methods -- 3 Our Approach -- 4 Experiments -- 4.1 Datasets -- 4.2 Baseline Methods -- 4.3 Evaluation Procedure -- 4.4 Results -- 5 Conclusion and Future Work -- References -- Privacy-Preserving in Double Deep-Q-Network with Differential Privacy in Continuous Spaces -- 1 Introduction -- 2 Preliminaries -- 2.1 Double Deep Q Network -- 2.2 Differential Privacy -- 3 Differentially Private Double Deep Q Network -- 3.1 Overview of Our Method -- 3.2 The Algorithm Design -- 3.3 Rationale of Using DPSGD -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Result and Analysis -- 5 Conclusion -- References -- HESIP: A Hybrid System for Explaining Sub-symbolic Predictions -- 1 Introduction -- 2 The LIME-Aleph System -- 3 The HESIP System Architecture -- 4 Ontology for HESIP -- 5 Image Information Extraction -- 6 Learning Rules in cplint -- 7 Applying HESIP to a New Problem Domain -- 8 Generating Explanations -- 9 Experiments -- 10 Comparison -- 11 Conclusion -- References -- An Explainable Recommendation Based on Acyclic Paths in an Edge-Colored Graph -- 1 Introduction -- 2 Preliminary -- 3 Proposed Method -- 3.1 Graph Construction -- 3.2 Acyclic-Path-Based Recommendation -- 3.3 Explanation by Color Sequences -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Knowledge Transfer for Deep Reinforcement Agents in General Game Playing -- 1 Introduction -- 2 Background -- 3 Transfer Learning in Deep RL General Game-Playing Agents -- 3.1 Simple Network Transfer in General Game Playing -- 3.2 Complex Network Transfer -- 3.3 Multitask Training for General Game Playing.
4 Experimental Evaluation -- 4.1 Generic Agent Designs -- 4.2 Game Variations -- 4.3 Evaluation Methodology -- 5 Results and Discussion -- 5.1 Single Network Agents -- 5.2 Complex Network Transfer -- 5.3 Multi-network Agents -- 6 Conclusion and Future Work -- References -- GSMI: A Gradient Sign Optimization Based Model Inversion Method -- 1 Introduction -- 2 Gradient Sign Model Inversion -- 2.1 Threat model -- 2.2 Overview of the Attack -- 2.3 Proposed Model Inversion: GSMI -- 2.4 Two-Pass Components Selection -- 3 Performance Evaluation -- 3.1 Experimental Setup -- 3.2 Results -- 3.3 Discussion -- 4 Related Work -- 5 Summary and Future Work -- References -- Multicollinearity Correction and Combined Feature Effect in Shapley Values -- 1 Introduction -- 2 Proposed Method -- 2.1 MCC Shapley Values for Individual Features -- 2.2 MCC Shapley Values for Combination of Two or More Features -- 2.3 Algorithm of MCC Shapley Value Calculation -- 3 Results -- 3.1 Dataset - House Prices -- 4 Conclusion -- References -- Does a Face Mask Protect My Privacy?: Deep Learning to Predict Protected Attributes from Masked Face Images -- 1 Introduction -- 2 Related Work -- 2.1 Biometrics and Privacy -- 2.2 Face Biometric and Masks -- 2.3 User Perception -- 3 Methodology -- 3.1 User Perception Survey -- 3.2 Dataset and Synthetic Mask Generation -- 3.3 Computer Vision Workflow -- 3.4 Privacy Vulnerability Index(PVI) -- 4 Evaluation Results -- 4.1 User Perception Study -- 4.2 Prediction Accuracy -- 4.3 Impact of Image Attributes -- 4.4 Privacy Invasiveness -- 5 Discussion and Conclusion -- 5.1 Predicting Protected Attributes -- 5.2 Biases from Image Attributes -- 5.3 Privacy Preservation -- 5.4 Limitations -- 5.5 Conclusion and Future Work -- References -- Representation-Induced Algorithmic Bias -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References. Contextual Importance and Utility: A Theoretical Foundation -- 1 Introduction -- 2 Theory -- 2.1 Additive Feature Attribution Methods -- 2.2 Decision Theory and Multi-attribute Utility Theory -- 2.3 Contextual Importance and Utility (CIU) -- 2.4 Contextual Influence -- 2.5 CIU Versus Additive Feature Attribution Methods -- 3 Experimental Evaluation -- 4 Conclusion -- References -- Deeper Insights into Neural Nets with Random Weights -- 1 Introduction -- 2 Literature Review on Polynomial Approximations of Activation Functions -- 3 Analysis -- 4 Simulations -- 5 Conclusions -- References -- Applications -- De Novo Molecular Generation with Stacked Adversarial Model -- 1 Introduction -- 2 Related Works -- 2.1 Generative Adversarial Models -- 2.2 Generative Models for Drug Discovery -- 3 Stacked Bidirectional Adversarial Autoencoder -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Experimental Setup -- 4.3 Experimental Evaluations -- 5 Conclusion -- References -- Tailoring Contact Based Scoring Functions for Protein Structure Prediction -- 1 Introduction -- 2 Preliminaries -- 3 Scoring Functions -- 3.1 Existing Scoring Functions -- 3.2 Proposed Scoring Functions -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Comparison of Scoring Functions -- 4.3 Comparison with Existing Methods -- 5 Conclusions -- References -- Evaluation of Deep Learning Techniques on a Novel Hierarchical Surgical Tool Dataset -- 1 Introduction -- 2 Class Hierarchies and Training Strategies -- 3 Methodology -- 3.1 Surgery Dataset -- 3.2 Surgery Hierarchy -- 3.3 CNN Training Strategies -- 3.4 Metrics Reported -- 4 Experiments and Results -- 4.1 Does Size Matter? -- 4.2 Class Frequencies -- 5 Conclusions and Future Work -- References -- Feature Extraction Using Wavelet Scattering Transform Coefficients for EMG Pattern Classification -- 1 Introduction. 2 Wavelet Scattering Transform -- 3 Data Acquisition -- 4 Results -- 4.1 Results of BioPatrec-Database -- 4.2 Results of Force-Database -- 4.3 Results of 3DC-Database -- 5 Conclusion -- References -- Modelling Eye-Gaze Movement Using Gaussian Auto-regression Hidden Markov -- 1 Introduction -- 2 Preliminaries -- 2.1 Preparation for Data Collection -- 2.2 Data Collection -- 2.3 Data Pre-processing -- 3 Methodology of Eye Gaze Predictive Modelling -- 3.1 Image Transform -- 3.2 Gaussian Auto-regression Hidden Markov -- 4 Results and Analysis -- 4.1 Eye Gaze Inducted Dynamic Changes -- 4.2 Prediction Performance -- 4.3 Training and Test -- 4.4 Accuracy Analysis -- 5 Conclusion -- References -- Strategies Improve Social Welfare: An Empirical Study of Strategic Voting in Social Networks -- 1 Introduction -- 1.1 Related Work -- 2 Model -- 2.1 Basic Notations and Definitions -- 2.2 Decision Models from the Literature -- 2.3 AU Revised Model -- 2.4 The Iterative Voting Process -- 3 Experiments -- 3.1 Experiment Settings -- 3.2 Results -- 4 Conclusion -- References -- A Network-Based Rating Mechanism Against False-Name Attack -- 1 Introduction -- 2 The Model -- 3 Weighted Rating Mechanism -- 4 Conclusion -- References -- Modular Construction Planning Using Graph Neural Network Heuristic Search -- 1 Introduction -- 2 Related work -- 2.1 Neural Search Based Planning -- 2.2 Graph Generation with Neural Networks -- 3 Problem Formulation -- 4 Approach -- 4.1 Search as Planning and Design -- 4.2 Consistency of the Training Heuristic -- 5 Data Generation and Training -- 5.1 Data Augmentation with Adjacent States -- 5.2 Training -- 6 Performance Evaluation -- 6.1 Ablation Evaluation for Synthetic Data Augmentation -- 7 Conclusions -- References -- Priority-Based Traffic Management Protocols for Autonomous Vehicles on Road Networks -- 1 Introduction. 2 Road Network Modelling -- 3 Priority-Based Traffic Management Protocols -- 3.1 Static Priority Management Protocol -- 3.2 Dynamic Priority Management Protocol -- 3.3 Vehicle-Based Priority Management Protocol -- 4 Experimental Setting and Results -- 4.1 Average Delay for the Static-Priority Management Protocol -- 4.2 Bullwhip Effect for the Static Priority Management Protocol -- 4.3 Average Delay for Different Management Protocols -- 4.4 Latency Function -- 5 Related Work and Conclusion -- References -- Improving Traffic Load Prediction with Multi-modality -- 1 Introduction -- 2 Proposed Method -- 2.1 Mathematical Formulation -- 2.2 Multi-modal Method -- 3 Data Collection and Pre-processing -- 3.1 Multi-modal Data -- 3.2 Traffic Data -- 3.3 Experiment -- 4 Discussion -- 5 Related Works -- 6 Conclusion and Future Works -- References -- Predicting Geological Material Types Using Ground Penetrating Radar -- 1 Introduction -- 2 Background -- 2.1 Site Geology -- 2.2 Interaction of Site Materials and GPR -- 2.3 Machine Learning and Feature Extraction -- 3 Gaussian Ridge Extraction -- 4 Methodology -- 4.1 Signal Segmentation and Classification Process -- 4.2 Feature Extraction Processes -- 4.3 Training and Testing of Machine Learning Models -- 5 Results and Discussion -- 5.1 Individual Feature Extraction Analysis -- 5.2 Concatenation of Features into Combined Feature Space -- 5.3 Application of Feature Selection and Majority Voting -- 6 Conclusions and Future Works -- References -- A Gated Recurrent Neural Network for Electric Vehicle Detection with Imbalanced Samples -- 1 Introduction -- 2 Imbalanced Data Processing -- 2.1 Dynamic Time Warping -- 2.2 DTW Constraints -- 3 Gated Recurrent Units Network -- 4 Empirical Study -- 4.1 Data Preparation -- 4.2 The GRU Network Trianing and Validation -- 5 Conclusion -- References. User-Defined Smart Contracts Using Answer Set Programming. |
| Record Nr. | UNISA-996464450403316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Complex Systems and Networks : Dynamics, Controls and Applications / / edited by Jinhu Lü, Xinghuo Yu, Guanrong Chen, Wenwu Yu
| Complex Systems and Networks : Dynamics, Controls and Applications / / edited by Jinhu Lü, Xinghuo Yu, Guanrong Chen, Wenwu Yu |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (VIII, 482 p. 196 illus., 158 illus. in color.) |
| Disciplina | 004.21 |
| Collana | Understanding Complex Systems |
| Soggetto topico |
Computational complexity
Physics Statistical physics Complexity Applications of Graph Theory and Complex Networks Applications of Nonlinear Dynamics and Chaos Theory |
| ISBN | 3-662-47824-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Discovering Cluster Dynamics Using Kernel Spectral Methods -- Community Detection in Bipartite Networks: Algorithms and Case Studies -- Epidemiological Modeling on Complex Networks -- Resilience of Spatial Networks -- Synchronization and Control of Hyper and Colored Networks -- New Nonlinear CPRNG Based on Tent and Logistic Maps -- Distributed Finite-time Cooperative Control of Multi-agent Systems -- Composite Finite-time Containment Control for Disturbed Second-order multi-agent Systems.-Application of Fractional-order Calculus in a Class of Multi-Agent System -- Chaos Control and Anticontrol of Complex Systems via Parrondo’s Game -- Collective Behavior Coordination with Predictive Mechanisms -- Convergence, Consensus and Synchronization of Complex Networks via Contraction Theory -- Towards Structural Controllability of Temporal Complex Networks -- A General Model for Studying Time Evolution of Transition Networks -- Deflection Routing in Complex Networks -- Recommender Systems for Social Networks Analysis and Mining:Precision vs. Diversity -- Strategy Selection in Networked Evolutionary Games: Structural Effect and the Evolution of Cooperation -- Network Analysis, Integration and Methods in Computational Biology. |
| Record Nr. | UNINA-9910254183803321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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