Advanced Energy Storage Technologies and Their Applications (AESA) / / edited by Rui Xiong, Hailong Li, Joe (Xuan) Zhou
| Advanced Energy Storage Technologies and Their Applications (AESA) / / edited by Rui Xiong, Hailong Li, Joe (Xuan) Zhou |
| Pubbl/distr/stampa | Basel, Switzerland : , : MDPI, , 2018 |
| Descrizione fisica | 1 online resource (426 pages) : illustrations |
| Disciplina | 621.47 |
| Soggetto topico | Solar energy |
| ISBN | 3-03842-545-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | About the Special Issue Editors -- Preface to "Advanced Energy Storage Technologies and Their Applications (AESA)" -- Rui Xiong, Hailong Li and Xuan Zhou Advanced Energy Storage Technologies and Their Applications (AESA2017) Reprinted from: Energies 2017, 10(9), 1366; doi: 10.3390/en10091366 -- Linhai Liu, Baoshan Zhu, Li Bai, Xiaobing Liu and Yue Zhao Parametric Design of an Ultrahigh-Head Pump-Turbine Runner Based on Multiobjective Optimization, Reprinted from: Energies 2017, 10(8), 1169; doi: 10.3390/en10081169 -- Xiaogang Wu, Zhe Chen and Zhiyang Wang Analysis of Low Temperature Preheating Effect Based on Battery Temperature-Rise Model, Reprinted from: Energies 2017, 10(8), 1121; doi:10.3390/10081121 -- Hossein Safaei and Michael J. Aziz Thermodynamic Analysis of Three Compressed Air Energy Storage Systems: Conventional, Adiabatic, and Hydrogen-Fueled Reprinted from: Energies 2017, 10(7), 1020; doi: 10.3390/en10071020 -- Jichao Hong, Zhenpo Wang and Peng Liu Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles on Road Reprinted from: Energies 2017, 10(7), 919; doi: 10.3390/en10070919 -- Xiaogang Wu and Tianze Wang Optimization of Battery Capacity Decay for Semi-Active Hybrid Energy Storage System Equipped on Electric City Bus Reprinted from: Energies 2017, 10(6), 792; doi: 10.3390/en10060792 -- Chengning Zhang, Xin Jin and Junqiu Li PTC Self-Heating Experiments and Thermal Modeling of Lithium-Ion Battery Pack in Electric Vehicles Reprinted from: Energies 2017, 10(4), 572; doi: 10.3390/en10040572 -- Xiaofeng Ding, Jiawei Cheng and Feida Chen Impact of Silicon Carbide Devices on the Powertrain Systems in Electric Vehicles Reprinted from: Energies 2017, 10(4), 533; doi: 10.3390/en10040533 -- Jing Sun, Guojing Xing and Chenghui Zhang Data-Driven Predictive Torque Coordination Control during Mode Transition Process of Hybrid Electric Vehicles Reprinted from: Energies 2017, 10(4), 441; doi: 10.3390/en10040441 -- Yonggang Liu, Jie Li, Ming Ye, Datong Qin, Yi Zhang and Zhenzhen Lei Optimal Energy Management Strategy for a Plug-in Hybrid Electric Vehicle Based Grade Information Reprinted from: Energies 2017, 10(4), 412; doi: 10.3390/en10040412 -- Bo Jiang, Haifeng Dai, Xuezhe Wei, Letao Zhu and Zechang Sun Online Reliable Peak Charge/Discharge Power Estimation of Series-Connected Lithium-Ion Battery Packs Reprinted from: Energies 2017, 10(3), 390; doi: 10.3390/en10030390 -- Xiaofeng Ding, Min Du, Jiawei Cheng, Feida Chen, Suping Ren and Hong Guo Impact of Silicon Carbide Devices on the Dynamic Performance of Permanent Magnet Synchronous Motor Drive Systems for Electric Vehicles Reprinted from: Energies 2017, 10(3), 364; doi: 10.3390/en10030364 -- Sebastian Kuboth, Andreas König-Haagen and Dieter Brüggemann Numerical Analysis of Shell-and-Tube Type Latent Thermal Energy Storage Performance with Different Arrangements of Circular Fins Reprinted from: Energies 2017, 10(3), 274; doi: 10.3390/en10030274 -- Yunlong Shang, Qi Zhang, Naxin Cui and Chenghui Zhang A Cell-to-cell Equalizer Based on Three-Resonant-State Switched-Capacitor Converters for Series- Connected Battery Strings Reprinted from: Energies 2017, 10(2), 206; doi: 10.3390/en10020206 -- Xin Wang, Jun Yang, Lei Chen and Jifeng He Application of Liquid Hydrogen with SMES for Efficient Use of Renewable Energy in the Energy Internet Reprinted from: Energies 2017, 10(2), 185; doi: 10.3390/en10020185 -- Zijie Wang, Baoshan Zhu, Xuhe Wang and Daqing Qin Pressure Fluctuations in the S-Shaped Region of a Reversible Pump-Turbine Reprinted from: Energies 2017, 10(1), 96; doi: 10.3390/en10010096 -- Jiangong Zhu, Zechang Sun, Xuezhe Wei and Haifeng Dai Battery Internal Temperature Estimation for LiFePO. Battery Based on Impedance Phase Shift under Operating Conditions Reprinted from: Energies 2017, 10(1), 60; doi: 10.3390/en10010060 -- Zhenzhen Lei, Dong Cheng, Yonggang Liu, Datong Qin, Yi Zhang and Qingbo Xie A Dynamic Control Strategy for Hybrid Electric Vehicles Based on Parameter Optimization for Multiple Driving Cycles and Driving Pattern Recognition Reprinted from: Energies 2017, 10(1), 54; doi: 10.3390/en10010054 -- Jufeng Yang, Bing Xia, Yunlong Shang, Wenxin Huang and Chris Mi Improved Battery Parameter Estimation Method Considering Operating Scenarios for HEV/EV Applications Reprinted from: Energies 2017, 10(1), 5; doi: 10.3390/en10010005 -- Caiping Zhang, Jiuchun Jiang, Linjing Zhang, Sijia Liu, Leyi Wang and Poh Chiang Loh A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery Reprinted from: Energies 2016, 9(11), 900; doi:10.3390/9110900 -- Copyrighted materi Dafen Chen, Jiuchun Jiang, Xue Li, Zhanguo Wang and Weige Zhang Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis Reprinted from: Energies 2016, 9(11), 865; doi: 10.3390/en9110865 -- Michael Lanahan and Paulo Cesar Tabares-Velasco Seasonal Thermal-Energy Storage: A Critical Review on BTES Systems, Modeling, and System Design for Higher System Efficiency Reprinted from: Energies 2017, 10(6), 743; doi: 10.3390/en10060743 -- Roberto Benato, Gianluca Bruno, Francesco Palone, Rosario M. Polito and Massimo Rebolini Large-Scale Electrochemical Energy Storage in High Voltage Grids: Overview of the Italian Experience Reprinted from: Energies 2017, 10(1), 108; doi: 10.3390/en10010108. |
| Altri titoli varianti | Advanced Energy Storage Technologies and Their Applications |
| Record Nr. | UNINA-9910688456603321 |
| Basel, Switzerland : , : MDPI, , 2018 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multivariate and probabilistic analyses of sensory science problems [[electronic resource] /] / Jean-François Meullenet, Rui Xiong, and Christopher J. Findlay
| Multivariate and probabilistic analyses of sensory science problems [[electronic resource] /] / Jean-François Meullenet, Rui Xiong, and Christopher J. Findlay |
| Autore | Meullenet J.-F (Jean-Francois), <1968-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | [Chicago, Ill.], : IFT Press |
| Descrizione fisica | 1 online resource (258 p.) |
| Disciplina | 664/.07 |
| Altri autori (Persone) |
XiongRui
FindlayChristopher J |
| Collana | IFT Press |
| Soggetto topico |
Food - Sensory evaluation - Statistical methods
Multivariate analysis |
| ISBN |
1-282-36555-X
9786612365553 0-470-27753-X 1-61583-205-X 0-470-27631-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Multivariate and Probabilistic Analyses of Sensory Science Problems; Table of Contents; Introduction; Chapter 1. A Description of Sample Data Sets Used in Further Chapters; 1.1. A Description of Example Data Sets; References; Chapter 2. Panelist and Panel Performance: A Multivariate Experience; 2.1. The Multivariate Nature of Sensory Evaluation; 2.2. Univariate Approaches to Panelist Assessment; 2.3. Multivariate Techniques for Panelist Performance; 2.4. Panel Evaluation through Multivariate Techniques; 2.5. Conclusions; References; Chapter 3. A Nontechnical Description of Preference Mapping
3.1. Introduction 3.2. Internal Preference Mapping; 3.3. External Preference Mapping; 3.4. Conclusions; References; Chapter 4. Deterministic Extensions to Preference Mapping Techniques; 4.1. Introduction; 4.2. Application and Models Available; 4.3. Conclusions; References; Chapter 5. Multidimensional Scaling and Unfolding and the Application of Probabilistic Unfolding to Model Preference Data; 5.1. Introduction; 5.2. Multidimensional Scaling (MDS) and Unfolding; 5.3. Probabilistic Approach to Unfolding and Identifying the Drivers of Liking; 5.4. Examples; References Chapter 6. Consumer Segmentation Techniques 6.1. Introduction; 6.2. Methods Available; 6.3. Segmentation Methods Using Hierarchical Cluster Analysis; References; Chapter 7. Ordinal Logistic Regression Models in Consumer Research; 7.1. Introduction; 7.2. Limitations of Ordinary Least Squares Regression; 7.3. Odds, Odds Ratio, and Logit; 7.4. Binary Logistic Regression; 7.5. Ordinal Logistic Regression Models; 7.6. Porportional Odds Model (POM); 7.7. Conclusions; References; Chapter 8. Risk Assessment in Sensory and Consumer Science; 8.1. Introduction 8.2. Concepts of Quantitative Risk Assessment 8.3. A Case Study: Cheese Sticks Appetizers; 8.4. Conclusions; References; Chapter 9. Application of MARS to Preference Mapping; 9.1. Introduction; 9.2. MARS Basics; 9.3. Setting Control Parameters and Refining Models; 9.4. Example of Application of MARS; 9.5. A Comparison with PLS Regression; References; Chapter 10. Analysis of Just About Right Data; 10.1. Introduction; 10.2. Basics of Penalty Analysis; 10.3. Boot strapping Penalty Analysis; 10.4. Use of MARS to Model JAR Data; 10.5. A Proportional Odds/Hazards Approach to Diagnostic Data Analysis 10.6. Use of Dummy Variables to Model JAR DataReferences; Index |
| Record Nr. | UNISA-996199251203316 |
Meullenet J.-F (Jean-Francois), <1968->
|
||
| [Chicago, Ill.], : IFT Press | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Multivariate and probabilistic analyses of sensory science problems [[electronic resource] /] / Jean-François Meullenet, Rui Xiong, and Christopher J. Findlay
| Multivariate and probabilistic analyses of sensory science problems [[electronic resource] /] / Jean-François Meullenet, Rui Xiong, and Christopher J. Findlay |
| Autore | Meullenet J.-F (Jean-Francois), <1968-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | [Chicago, Ill.], : IFT Press |
| Descrizione fisica | 1 online resource (258 p.) |
| Disciplina | 664/.07 |
| Altri autori (Persone) |
XiongRui
FindlayChristopher J |
| Collana | IFT Press |
| Soggetto topico |
Food - Sensory evaluation - Statistical methods
Multivariate analysis |
| ISBN |
1-282-36555-X
9786612365553 0-470-27753-X 1-61583-205-X 0-470-27631-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Multivariate and Probabilistic Analyses of Sensory Science Problems; Table of Contents; Introduction; Chapter 1. A Description of Sample Data Sets Used in Further Chapters; 1.1. A Description of Example Data Sets; References; Chapter 2. Panelist and Panel Performance: A Multivariate Experience; 2.1. The Multivariate Nature of Sensory Evaluation; 2.2. Univariate Approaches to Panelist Assessment; 2.3. Multivariate Techniques for Panelist Performance; 2.4. Panel Evaluation through Multivariate Techniques; 2.5. Conclusions; References; Chapter 3. A Nontechnical Description of Preference Mapping
3.1. Introduction 3.2. Internal Preference Mapping; 3.3. External Preference Mapping; 3.4. Conclusions; References; Chapter 4. Deterministic Extensions to Preference Mapping Techniques; 4.1. Introduction; 4.2. Application and Models Available; 4.3. Conclusions; References; Chapter 5. Multidimensional Scaling and Unfolding and the Application of Probabilistic Unfolding to Model Preference Data; 5.1. Introduction; 5.2. Multidimensional Scaling (MDS) and Unfolding; 5.3. Probabilistic Approach to Unfolding and Identifying the Drivers of Liking; 5.4. Examples; References Chapter 6. Consumer Segmentation Techniques 6.1. Introduction; 6.2. Methods Available; 6.3. Segmentation Methods Using Hierarchical Cluster Analysis; References; Chapter 7. Ordinal Logistic Regression Models in Consumer Research; 7.1. Introduction; 7.2. Limitations of Ordinary Least Squares Regression; 7.3. Odds, Odds Ratio, and Logit; 7.4. Binary Logistic Regression; 7.5. Ordinal Logistic Regression Models; 7.6. Porportional Odds Model (POM); 7.7. Conclusions; References; Chapter 8. Risk Assessment in Sensory and Consumer Science; 8.1. Introduction 8.2. Concepts of Quantitative Risk Assessment 8.3. A Case Study: Cheese Sticks Appetizers; 8.4. Conclusions; References; Chapter 9. Application of MARS to Preference Mapping; 9.1. Introduction; 9.2. MARS Basics; 9.3. Setting Control Parameters and Refining Models; 9.4. Example of Application of MARS; 9.5. A Comparison with PLS Regression; References; Chapter 10. Analysis of Just About Right Data; 10.1. Introduction; 10.2. Basics of Penalty Analysis; 10.3. Boot strapping Penalty Analysis; 10.4. Use of MARS to Model JAR Data; 10.5. A Proportional Odds/Hazards Approach to Diagnostic Data Analysis 10.6. Use of Dummy Variables to Model JAR DataReferences; Index |
| Record Nr. | UNINA-9910144391303321 |
Meullenet J.-F (Jean-Francois), <1968->
|
||
| [Chicago, Ill.], : IFT Press | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multivariate and probabilistic analyses of sensory science problems / / Jean-Francois Meullenet, Rui Xiong, and Christopher J. Findlay
| Multivariate and probabilistic analyses of sensory science problems / / Jean-Francois Meullenet, Rui Xiong, and Christopher J. Findlay |
| Autore | Meullenet J.-F (Jean-Francois), <1968-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | [Chicago, Ill.], : IFT Press |
| Descrizione fisica | 1 online resource (258 p.) |
| Disciplina | 664/.07 |
| Altri autori (Persone) |
XiongRui
FindlayChristopher J |
| Collana | IFT Press |
| Soggetto topico |
Food - Sensory evaluation - Statistical methods
Multivariate analysis |
| ISBN |
9786612365553
9781282365551 128236555X 9780470277539 047027753X 9781615832057 161583205X 9780470276310 0470276312 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Multivariate and Probabilistic Analyses of Sensory Science Problems; Table of Contents; Introduction; Chapter 1. A Description of Sample Data Sets Used in Further Chapters; 1.1. A Description of Example Data Sets; References; Chapter 2. Panelist and Panel Performance: A Multivariate Experience; 2.1. The Multivariate Nature of Sensory Evaluation; 2.2. Univariate Approaches to Panelist Assessment; 2.3. Multivariate Techniques for Panelist Performance; 2.4. Panel Evaluation through Multivariate Techniques; 2.5. Conclusions; References; Chapter 3. A Nontechnical Description of Preference Mapping
3.1. Introduction 3.2. Internal Preference Mapping; 3.3. External Preference Mapping; 3.4. Conclusions; References; Chapter 4. Deterministic Extensions to Preference Mapping Techniques; 4.1. Introduction; 4.2. Application and Models Available; 4.3. Conclusions; References; Chapter 5. Multidimensional Scaling and Unfolding and the Application of Probabilistic Unfolding to Model Preference Data; 5.1. Introduction; 5.2. Multidimensional Scaling (MDS) and Unfolding; 5.3. Probabilistic Approach to Unfolding and Identifying the Drivers of Liking; 5.4. Examples; References Chapter 6. Consumer Segmentation Techniques 6.1. Introduction; 6.2. Methods Available; 6.3. Segmentation Methods Using Hierarchical Cluster Analysis; References; Chapter 7. Ordinal Logistic Regression Models in Consumer Research; 7.1. Introduction; 7.2. Limitations of Ordinary Least Squares Regression; 7.3. Odds, Odds Ratio, and Logit; 7.4. Binary Logistic Regression; 7.5. Ordinal Logistic Regression Models; 7.6. Porportional Odds Model (POM); 7.7. Conclusions; References; Chapter 8. Risk Assessment in Sensory and Consumer Science; 8.1. Introduction 8.2. Concepts of Quantitative Risk Assessment 8.3. A Case Study: Cheese Sticks Appetizers; 8.4. Conclusions; References; Chapter 9. Application of MARS to Preference Mapping; 9.1. Introduction; 9.2. MARS Basics; 9.3. Setting Control Parameters and Refining Models; 9.4. Example of Application of MARS; 9.5. A Comparison with PLS Regression; References; Chapter 10. Analysis of Just About Right Data; 10.1. Introduction; 10.2. Basics of Penalty Analysis; 10.3. Boot strapping Penalty Analysis; 10.4. Use of MARS to Model JAR Data; 10.5. A Proportional Odds/Hazards Approach to Diagnostic Data Analysis 10.6. Use of Dummy Variables to Model JAR DataReferences; Index |
| Record Nr. | UNINA-9910828254203321 |
Meullenet J.-F (Jean-Francois), <1968->
|
||
| [Chicago, Ill.], : IFT Press | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 1 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han
| Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 1 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (VII, 242 p. 163 illus., 147 illus. in color.) |
| Disciplina | 621.3 |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico |
Electrical engineering
Artificial intelligence Electric power production Electric power distribution Electrical and Electronic Engineering Artificial Intelligence Mechanical Power Engineering Energy Grids and Networks |
| ISBN | 981-9648-56-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Intelligent Layout and Routing of Power Electronic Converters: A Technical Review and Cutting-edge Exploration -- Chapter 2. Economic Optimal Scheduling of Integrated Energy System based on improved DQN algorithm -- Chapter 3. Research and Simulation on Fault Location of Multi branch Distribution Network Based on Micro PMU -- Chapter 4. An Intelligent Optimization Method for Transcranial Magnetic Stimulation Waveforms to Improve Stimulation Selectivity. |
| Record Nr. | UNINA-9910997095203321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 2 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han
| Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 2 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (X, 578 p. 358 illus., 281 illus. in color.) |
| Disciplina | 621.3 |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico |
Electrical engineering
Artificial intelligence Electric power production Electric power distribution Electrical and Electronic Engineering Artificial Intelligence Mechanical Power Engineering Energy Grids and Networks |
| ISBN | 981-9640-63-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Global Efficiency Optimization of High-Gain IPOP System Based on Genetic Algorithm -- Chapter 2. IGBT Open-Circuit Fault Diagnosis of MMC Submodules Based on Tensor Data-Driven Approach -- Chapter 3. Study on the diagnosis of industrial robot abnormalities based on SVDD -- Chapter 4. Small defect detection of power electronic devices based on YOLO-DHGC -- Chapter 5. Research on Parallel Multimodal Current Sharing Based on Merged Coupled Inductance -- Chapter 6. Study on Fault Diagnosis of Power Electronic Devices in Power Conversion System Based on Machine Learning -- Chapter 7. Power Electronics Topology Derivation: A Technical Review and Cutting-edge Exploration. |
| Record Nr. | UNINA-9910996482803321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 3 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han
| Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 3 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (IX, 435 p. 257 illus., 221 illus. in color.) |
| Disciplina | 621.3 |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico |
Electrical engineering
Artificial intelligence Electric power production Electric power distribution Electrical and Electronic Engineering Artificial Intelligence Mechanical Power Engineering Energy Grids and Networks |
| ISBN | 981-9640-67-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Global Efficiency Optimization of High-Gain IPOP System Based on Genetic Algorithm -- Chapter 2. IGBT Open-Circuit Fault Diagnosis of MMC Submodules Based on Tensor Data-Driven Approach -- Chapter 3. Study on the diagnosis of industrial robot abnormalities based on SVDD -- Chapter 4. Small defect detection of power electronic devices based on YOLO-DHGC -- Chapter 5. Research on Parallel Multimodal Current Sharing Based on Merged Coupled Inductance -- Chapter 6. Study on Fault Diagnosis of Power Electronic Devices in Power Conversion System Based on Machine Learning -- Chapter 7. Power Electronics Topology Derivation: A Technical Review and Cutting-edge Exploration. |
| Record Nr. | UNINA-9910999692403321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 4 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han
| Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 4 : EAIC 2024, 6-8 December, Nanjing, China / / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (IX, 481 p. 236 illus., 190 illus. in color.) |
| Disciplina | 621.3 |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico |
Electrical engineering
Artificial intelligence Electric power production Electric power distribution Electrical and Electronic Engineering Artificial Intelligence Mechanical Power Engineering Energy Grids and Networks |
| ISBN | 981-9640-59-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Improved Integrated Energy Systems Multi-Energy Load Deep Learning Joint Prediction Method Based On CEEMDAN -- Chapter 2. An Evaluation Method for Micro-Energy Networks Participating in the Electricity-Hydrogen Market Based on Cloud Model -- Chapter 3. Robust Optimisation Strategy For Distribution Of Integrated Energy Systems Considering Multiple Stakeholders -- Chapter 4. New Energy Power System Security and Stability Assessment Based on Apirori and Dynamic Weighted Cloud Model -- Chapter 5. A Review of Cluster Electric Vehicle Charging Scheduling Based on Multi-agent Deep Reinforcement Learning -- Chapter 6. Multi-Objective Optimization of Integrated Energy System Considering Double Uncertainty Of source and Load -- Chapter 7. False Data Injection Method Design for Power Sensors Based on Robust Principal Component Analysis -- Chapter 8. Key Technology of Joint Analysis of Cross-Modal Data for Integrated Service of Railroad Passenger Stations -- Chapter 9. A Two-step Soft Open Point Location And Capacity Determination Method Based On Power Flow Betweenness -- Chapter 10. Research on Intelligent Prediction Model of Ultra Short term Photovoltaic Power Generation Based on W-DA BiLSTM -- Chapter 11. Fault detection method of transmission sections based on GRU deep network -- Chapter 12. Construction and application of a grey prediction model based on periodical aggregation and periodical component factor -- Chapter 13. Research status and intelligent application of renewable energy hydrogen production and hydrogenation integrated station -- Chapter 14. Intelligent carbon emission accounting method based on deep learning algorithm -- Chapter 15. Remaining life prediction of motor bearing based on fusion degradation indicator -- Chapter 16. TD3 Deep Reinforcement Learning-Based Improved Sensorless MRAS Control Strategy for Multi-Electric Aircraft PMSM -- Chapter 17. Diagnosis of Interturn Short Circuit Faults in Switched Reluctance Machines Based on Parameter Optimized VMD and CNN-BiLST -- Chapter 18. YOLOv9-based Detection Method for Pyrotechnic Operations and Protective Equipment -- Chapter 19. Verification Method for Arc Suppression Coil Tracking Compensation Performance -- Chapter 20. Lithium battery SOC estimation based on BiLSTM MHSA -- Chapter 21. Neural Network-Based Adaptive Sliding Mode Control for Wheel Slip Ratio Control System -- Chapter 22. Comprehensive Decision-Making of Large-scale Rooftop Photovoltaic Access to Power Supply-guaranteed Microgrid -- Chapter 23. Trajectory planning of digital ray detection system for welding seam of double robot rocket tank based on MATLAB -- Chapter 24. Controllable Image Editing for Insulator Defect Generation and Detection -- Chapter 25. Topology Optimization of Offshore Wind Farm Collection System Based on Priority Queue Esau- Williams Algorith -- Chapter 26. Tabular image content reconstruction model for two- branch network design. Chapter 27. Volume Measurement Technology for Irregular Shaped Ice Cover Based on Multi-view 3D Reconstruction. |
| Record Nr. | UNINA-9910996491003321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||