Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Optimization techniques in engineering : advances and applications / / edited by Anita Khosla [and three others]
| Optimization techniques in engineering : advances and applications / / edited by Anita Khosla [and three others] |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., and Scrivener Publishing LLC, , [2023] |
| Descrizione fisica | 1 online resource (543 pages) |
| Disciplina | 620.0015118 |
| Collana | Sustainable Computing and Optimization Series |
| Soggetto topico | Engineering - Mathematical models |
| ISBN |
1-119-90639-3
1-119-90638-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgment -- Part 1: Soft Computing and Evolutionary-Based Optimization -- Chapter 1 Improved Grey Wolf Optimizer with Levy Flight to Solve Dynamic Economic Dispatch Problem with Electric Vehicle Profiles -- 1.1 Introduction -- 1.2 Problem Formulation -- 1.2.1 Power Output Limits -- 1.2.2 Power Balance Limits -- 1.2.3 Ramp Rate Limits -- 1.2.4 Electric Vehicles -- 1.3 Proposed Algorithm -- 1.3.1 Overview of Grey Wolf Optimizer -- 1.3.2 Improved Grey Wolf Optimizer with Levy Flight -- 1.3.3 Modeling of Prey Position with Levy Flight Distribution -- 1.4 Simulation and Results -- 1.4.1 Performance of Improved GWOLF on Benchmark Functions -- 1.4.2 Performance of Improved GWOLF for Solving DED for the Different Charging Probability Distribution -- 1.5 Conclusion -- References -- Chapter 2 Comparison of YOLO and Faster R-CNN on Garbage Detection -- 2.1 Introduction -- 2.2 Garbage Detection -- 2.2.1 Transfer Learning-Technique -- 2.2.2 Inception-Custom Model -- 2.3 Experimental Results -- 2.3.1 Results Obtained Using YOLO Algorithm -- 2.3.2 Results Obtained Using Faster R-CNN -- 2.4 Future Scope -- 2.5 Conclusion -- References -- Chapter 3 Smart Power Factor Correction and Energy Monitoring System -- 3.1 Introduction -- 3.2 Block Diagram -- 3.2.1 Power Factor Concept -- 3.2.2 Power Factor Calculation -- 3.3 Simulation -- 3.4 Conclusion -- References -- Chapter 4 ANN-Based Maximum Power Point Tracking Control Configured Boost Converter for Electric Vehicle Applications -- 4.1 Introduction -- 4.2 Block Diagram -- 4.3 ANN-Based MPPT for Boost Converter -- 4.4 Closed Loop Control -- 4.5 Simulation Results -- 4.6 Conclusion -- References -- Chapter 5 Single/Multijunction Solar Cell Model Incorporating Maximum Power Point Tracking Scheme Based on Fuzzy Logic Algorithm -- 5.1 Introduction.
5.2 Modeling Structure -- 5.2.1 Single-Junction Solar Cell Model -- 5.2.2 Modeling of Multijunction Solar PV Cell -- 5.3 MPPT Design Techniques -- 5.3.1 Design of MPPT Scheme Based on P& -- O Technique -- 5.3.2 Design of MPPT Scheme Based on FLA -- 5.4 Results and Discussions -- 5.4.1 Single-Junction Solar Cell -- 5.4.2 Multijunction Solar PV Cell -- 5.4.3 Implementation of MPPT Scheme Based on P& -- O Technique -- 5.4.4 Implementation of MPPT Scheme Based on FLA -- 5.5 Conclusion -- References -- Chapter 6 Particle Swarm Optimization: An Overview, Advancements and Hybridization -- 6.1 Introduction -- 6.2 The Particle Swarm Optimization: An Overview -- 6.3 PSO Algorithms and Pseudo-Code -- 6.3.1 PSO Algorithm -- 6.3.2 Pseudo-Code for PSO -- 6.3.3 PSO Limitations -- 6.4 Advancements in PSO and Its Perspectives -- 6.4.1 Inertia Weight -- 6.4.2 Constriction Factors -- 6.4.3 Topologies -- 6.4.4 Analysis of Convergence -- 6.5 Hybridization of PSO -- 6.5.1 PSO Hybridization with Artificial Bee Colony (ABC) -- 6.5.2 PSO Hybridization with Ant Colony Optimization (ACO) -- 6.5.3 PSO Hybridization with Genetic Algorithms (GA) -- 6.6 Area of Applications of PSO -- 6.7 Conclusions -- References -- Chapter 7 Application of Genetic Algorithm in Sensor Networks and Smart Grid -- 7.1 Introduction -- 7.2 Communication Sector -- 7.2.1 Sensor Networks -- 7.3 Electrical Sector -- 7.3.1 Smart Microgrid -- 7.4 A Brief Outline of GAs -- 7.5 Sensor Network's Energy Optimization -- 7.6 Sensor Network's Coverage and Uniformity Optimization Using GA -- 7.7 Use GA for Optimization of Reliability and Availability for Smart Microgrid -- 7.8 GA Versus Traditional Methods -- 7.9 Summaries and Conclusions -- References -- Chapter 8 AI-Based Predictive Modeling of Delamination Factor for Carbon Fiber-Reinforced Polymer (CFRP) Drilling Process -- 8.1 Introduction. 8.2 Methodology -- 8.3 AI-Based Predictive Modeling -- 8.3.1 Linear Regression -- 8.3.2 Random Forests -- 8.3.3 XGBoost -- 8.3.4 SVM -- 8.4 Performance Indices -- 8.4.1 Root Mean Squared Error (RMSE) -- 8.4.2 Mean Squared Error (MSE) -- 8.4.3 R2 (R-Squared) -- 8.5 Results and Discussion -- 8.5.1 Key Performance Metrics (KPIs) During the Model Training Phase -- 8.5.2 Key Performance Index Metrics (KPIs) During the Model Testing Phase -- 8.5.3 K Cross Fold Validation -- 8.6 Conclusions -- References -- Chapter 9 Performance Comparison of Differential Evolutionary Algorithm-Based Contour Detection to Monocular Depth Estimation for Elevation Classification in 2D Drone-Based Imagery -- 9.1 Introduction -- 9.2 Literature Survey -- 9.3 Research Methodology -- 9.3.1 Dataset and Metrics -- 9.4 Result and Discussion -- 9.5 Conclusion -- References -- Chapter 10 Bioinspired MOPSO-Based Power Allocation for Energy Efficiency and Spectral Efficiency Trade-Off in Downlink NOMA -- 10.1 Introduction -- 10.2 System Model -- 10.3 User Clustering -- 10.4 Optimal Power Allocation for EE-SE Tradeoff -- 10.4.1 Multiobjective Optimization Problem -- 10.4.2 Multiobjective PSO -- 10.4.3 MOPSO Algorithm for EE-SE Trade-Off in Downlink NOMA -- 10.5 Numerical Results -- 10.6 Conclusion -- References -- Chapter 11 Performances of Machine Learning Models and Featurization Techniques on Amazon Fine Food Reviews -- 11.1 Introduction -- 11.1.1 Related Work -- 11.2 Materials and Methods -- 11.2.1 Data Cleaning and Pre-Processing -- 11.2.2 Feature Extraction -- 11.2.3 Classifiers -- 11.3 Results and Experiments -- 11.4 Conclusion -- References -- Chapter 12 Optimization of Cutting Parameters for Turning by Using Genetic Algorithm -- 12.1 Introduction -- 12.2 Genetic Algorithm GA: An Evolutionary Computational Technique -- 12.3 Design of Multiobjective Optimization Problem. 12.3.1 Decision Variables -- 12.3.2 Objective Functions -- 12.3.3 Bounds of Decision Variables -- 12.3.4 Response Variables -- 12.4 Results and Discussions -- 12.4.1 Single Objective Optimization -- 12.4.2 Results of Multiobjective Optimization -- 12.5 Conclusion -- References -- Chapter 13 Genetic Algorithm-Based Optimization for Speech Processing Applications -- 13.1 Introduction to GA -- 13.1.1 Enhanced GA -- 13.2 GA in Automatic Speech Recognition -- 13.2.1 GA for Optimizing Off-Line Parameters in Voice Activity Detection (VAD) -- 13.2.2 Classification of Features in ASR Using GA -- 13.2.3 GA-Based Distinctive Phonetic Features Recognition -- 13.2.4 GA in Phonetic Decoding -- 13.3 Genetic Algorithm in Speech Emotion Recognition -- 13.3.1 Speech Emotion Recognition -- 13.3.2 Genetic Algorithms in Speech Emotion Recognition -- 13.4 Genetic Programming in Hate Speech Using Deep Learning -- 13.4.1 Introduction to Hate Speech Detection -- 13.4.2 GA Integrated With Deep Learning Models for Hate Speech Detection -- 13.5 Conclusion -- References -- Chapter 14 Performance of P, PI, PID, and NARMA Controllers in the Load Frequency Control of a Single-Area Thermal Power Plant -- 14.1 Introduction -- 14.2 Single-Area Power System -- 14.3 Automatic Load Frequency Control (ALFC) -- 14.4 Controllers Used in the Simulink Model -- 14.4.1 PID Controller -- 14.4.2 PI Controller -- 14.4.3 P Controller -- 14.5 Circuit Description -- 14.6 ANN and NARMA L2 Controller -- 14.7 Simulation Results and Comparative Analysis -- 14.8 Conclusion -- References -- Part 2: Decision Science and Simulation-Based Optimization -- Chapter 15 Selection of Nonpowered Industrial Truck for Small Scale Manufacturing Industry Using Fuzzy VIKOR Method Under FMCDM Environment -- 15.1 Introduction -- 15.2 Fuzzy Set Theory -- 15.2.1 Some Important Fuzzy Definitions -- 15.2.2 Fuzzy Operations. 15.2.3 Linguistic Variable (LV) -- 15.3 FVIKOR -- 15.4 Problem Definition -- 15.5 Results and Discussions -- 15.6 Conclusions -- References -- Chapter 16 Slightly and Almost Neutrosophic gsα*-Continuous Function in Neutrosophic Topological Spaces -- 16.1 Introduction -- 16.2 Preliminaries -- 16.3 Slightly Neutrosophic gsα* - Continuous Function -- 16.4 Almost Neutrosophic gsα* - Continuous Function -- 16.5 Conclusion -- References -- Chapter 17 Identification and Prioritization of Risk Factors Affecting the Mental Health of Farmers -- 17.1 Introduction -- 17.2 Materials and Methods -- 17.2.1 ELECTRE Technique -- 17.3 Result and Discussion -- 17.4 Conclusion -- References -- Chapter 18 Multiple Objective and Subjective Criteria Evaluation Technique (MOSCET): An Application to Material Handling System Selection -- 18.1 Introduction -- 18.2 Multiple Objective and Subjective Criteria Evaluation Technique (MOSCET): The Proposed Algorithm -- 18.3 Illustrative Example -- 18.3.1 Problem Definition -- 18.3.2 Calculation and Discussions -- 18.4 Conclusions -- References -- Chapter 19 Evaluation of Optimal Parameters to Enhance Worker's Performance in an Automotive Industry -- 19.1 Introduction -- 19.2 Methodology -- 19.3 Results and Discussion -- 19.4 Conclusions -- References -- Chapter 20 Determining Key Influential Factors of Rural Tourism-An AHP Model -- 20.1 Introduction -- 20.2 Rural Tourism -- 20.3 Literature Review -- 20.4 Objectives -- 20.5 Methodology -- 20.6 Analysis -- 20.7 Results and Discussion -- 20.8 Conclusions -- 20.9 Managerial Implications -- References -- Chapter 21 Solution of a Pollution-Based Economic Order Quantity Model Under Triangular Dense Fuzzy Environment -- 21.1 Introduction -- 21.1.1 Overview -- 21.1.2 Motivation and Specific Study -- 21.2 Preliminaries -- 21.2.1 Pollution Function -- 21.2.2 Triangular Dense Fuzzy Set (TDFS). 21.3 Notations and Assumptions. |
| Record Nr. | UNINA-9910830854903321 |
| Hoboken, NJ : , : John Wiley & Sons, Inc., and Scrivener Publishing LLC, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Renewable energy optimization, planning and control : proceedings of ICRTE 2022 / / Anita Khosla, Mohan Kolhe, editors
| Renewable energy optimization, planning and control : proceedings of ICRTE 2022 / / Anita Khosla, Mohan Kolhe, editors |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (467 pages) |
| Disciplina | 333.794 |
| Collana | Studies in infrastructure and control |
| Soggetto topico | Renewable energy sources |
| ISBN | 981-19-8963-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. A Socio Inspired Technique in Nuclear Power Plant for Load Frequency Control by using Cohort Intelligence Optimization-based PID Controller -- Chapter 2. Seamless and smooth power sharing, voltage and frequency Control of Islanded Microgrid with Droop cum Supervisory Controller -- Chapter 3. Genetic Algorithm for Economic Load Dispatchwith Microgrid to Save Environment by reduction of CO2 Emission -- Chapter 4. An Electric Vehicle Integration in Distributed Generation with an Island Detection Technique to Meet Critical Load and Non-Critical Load -- Chapter 5. Green Communications: A Review of the Current Situation -- Chapter 6. PV System Design and Solar Generation Implementation -- Chapter 7. CoviDistBand: IoT-based wearable smart band to ensure social distancing -- Chapter 8. Gesture Recognition Glove for Speech and Hearing Impaired people -- Chapter 9. Simulation and Analysis of Rural Energy Systems Based on MultiCriteria Decision Making Methods -- Chapter 10. Assessment of Sessional Solar Energy Using PVsyst and SAM -- Chapter 11. Power Generation using Municipal Solid Waste : A Review -- Chapter 12. Solar Power Probabilistic Prediction Using Random Forest Regressor -- Chapter 13. Impact of COVID-19 on Renewable Power Generation in India -- Chapter 14. Reference Model Design, Control and Reliability Analysis of PV Emulator -- Chapter 15. Smart Technologies in Indian Environment- A Critical review. |
| Record Nr. | UNINA-9910682586403321 |
| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Renewable energy optimization, planning and control Proceedings of ICRTE 2021 . Volume 1 / / Anita Khosla, Monika Aggarwal, editors
| Renewable energy optimization, planning and control Proceedings of ICRTE 2021 . Volume 1 / / Anita Khosla, Monika Aggarwal, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (188 pages) |
| Disciplina | 628 |
| Collana | Studies in Infrastructure and Control |
| Soggetto topico | Sustainable engineering |
| ISBN |
981-16-4663-5
981-16-4662-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 A Review on Power Quality İmprovement of Grid Connected PV with Lithium-Ion and Super Capacitor Based Hybrid Energy Storage System Using a New Control Strategy -- 1.1 Introduction -- 1.2 Lıterature Survey -- 1.3 Methodology -- 1.3.1 The Historic Data Processing for Solar Forecasting -- 1.3.2 Analysis of Variation of Solar, Load and the Sizing of Battery on a Hourly Basis -- 1.4 Block Diagram -- 1.4.1 Energy Storage Block -- 1.4.2 Mode of Operation -- 1.4.3 The Complete System -- 1.4.4 Model Description -- 1.4.5 Fuzzy Logic Control Flowchart -- 1.5 Conclusion -- References -- 2 Influence of Alternative Fuels on Exhaust Emissions of IC Engine: A Review -- 2.1 Introduction -- 2.2 Effect of Methanol on Engine Emissions -- 2.2.1 Effects on HC and NOx Emissions -- 2.2.2 Effects on CO and CO2 Emissions -- 2.3 Effect of Ethanol on Engine Emissions -- 2.3.1 Effects on HC and NOx Emissions -- 2.3.2 Effects on CO and CO2 Emissions -- 2.4 Effect of Hydrogen on Engine Emissions -- 2.4.1 Effects on HC and NOx Emissions -- 2.4.2 Effects on CO and CO2 Emissions -- 2.5 Effect of Compressed Natural Gas on Engine Emissions -- 2.5.1 Effects on HC and NOx Emissions -- 2.5.2 Effects on CO and CO2 Emissions -- 2.6 Effect of Liquid Petroleum Gas on Engine Emissions -- 2.6.1 Effects on HC and NOx Emissions -- 2.6.2 Effects on CO and CO2 Emissions -- 2.7 Conclusion -- References -- 3 Hybrid Energy System for an Academic Institution: A Case Study -- 3.1 Introduction -- 3.2 Design of Hybrid Power Systems -- 3.2.1 Study Location and Its Load Profile -- 3.2.2 Available Energy Resources -- 3.3 Modeling of System Reliability and System Cost -- 3.4 System Configurations -- 3.4.1 Configuration-I -- 3.4.2 Configuration-II -- 3.5 Result of Configurations -- 3.5.1 Configuration-I -- 3.5.2 Configuration-II.
3.6 Conclusion -- References -- 4 Challenges to Mini-Grids: An Alternative to Rural Electrification -- 4.1 Introduction -- 4.2 Mini-Grid -- 4.3 Community-Operated Mini-Grids -- 4.4 Improved Power Planning and Challenges -- 4.5 Conclusion -- References -- 5 Comparative Analysis of Family of Luo Converter for Renewable Energy Applications -- 5.1 Introduction -- 5.2 Methodology -- 5.3 Proposed Luo Converters -- 5.3.1 Elementary Luo Converter -- 5.3.2 Re-Lift Luo Converter -- 5.3.3 Fused Luo Converters -- 5.4 Maximum Power Point Tracking -- 5.5 Vector Control or Field-Oriented Control -- 5.6 Grid-Connected System -- 5.7 Comparison of Converters -- 5.8 Simulation Results -- 5.9 Simulation Model and Results of Photovoltaic-Fed Induction Motor -- 5.9.1 Simulation Model and Results of Hybrid Renewable Grid-Connected System -- 5.9.2 Conclusions -- References -- 6 Design and Modeling of L-Shape Piezoelectric Energy Harvester for Powering Deep Brain Stimulation System -- 6.1 Introduction -- 6.2 Modeling of L-Shape Piezoelectric Energy Harvester -- 6.2.1 Structure of L-Shape Piezoelectric Energy Harvester -- 6.2.2 Voltage and Power Equations of Piezoelectric Energy Harvester -- 6.3 Medical Application-Deep Brain Stimulation System (DBSS) -- 6.4 Results and Discussion -- 6.4.1 Variation of Design Variables-Length, Width, Thickness, and Mass Weight -- 6.4.2 Proof Mass Analysis-Rectangular, Cylinder, and L-Shapes -- 6.4.3 Load Analysis of L-Shape Piezoelectric Harvester -- 6.5 Conclusion -- References -- 7 Solar Irradiation Forecasting by Long-Short Term Memory Using Different Training Algorithms -- 7.1 Introduction -- 7.2 Theoretical Background -- 7.2.1 Long-Short Term Memory Network -- 7.2.2 Training Algorithms -- 7.3 Experimental Setup -- 7.3.1 Data Description -- 7.3.2 Methodology -- 7.4 Results and Analysis -- 7.5 Conclusion -- References. 8 Forecasting of Wind Speed by Using Deep Learning for Optimal Use of the Energy Produced by Wind Farms -- 8.1 Introduction -- 8.2 Wind Speed Dataset Used -- 8.3 Deep Learning -- 8.3.1 Convolutional Neural Network -- 8.4 Results and Discussion -- 8.5 Conclusions -- References -- 9 Analysis of Predictive Current Control Technique in Wind Energy Conversion System -- Abstract -- 9.1 Introduction -- 9.2 Introduction to Control and Modulation Techniques in Matrix Convertor -- 9.3 Applications of Predictive Control Strategies for Matrix Converters -- 9.4 Conclusion and Summary -- 9.5 Scope for Future Work -- References -- 10 Genetic Algorithm Based Intelligent Control Strategy for Multi-input Multi-output DC-DC Converter -- 10.1 Introduction -- 10.2 Working of MIMO Converter -- 10.3 Control Strategy -- 10.4 Simulation Results -- 10.5 Conclusion -- References -- 11 Wavelet Transform Based Comparative Analysis of Wind Speed Forecasting Techniques -- 11.1 Introduction -- 11.2 Forecasting Models -- 11.2.1 Simple Exponential Smoothing -- 11.2.2 Wavelet Transform Decomposition Technique -- 11.3 Results and Discussion -- 11.4 Conclusion -- References -- 12 Maximization of Energy Production from Sholayar Hydropower Plant in India -- 12.1 Introduction -- 12.2 Multi-Reservoir Framework and Maximization of Hydropower Generation -- 12.2.1 Case Study-Sholayar Powerhouse -- 12.3 Results and Discussion -- 12.4 Conclusion -- References -- 13 Cuk-Based Single-Phase Inverter Design for PV Array Systems -- 13.1 Introduction -- 13.2 System Description -- 13.3 System Analysis -- 13.4 Maximum Power Point Tracking Controller -- 13.5 Simulation and Results -- 13.6 Conclusion -- References -- 14 Support Vector Machine Based Forecasting for Renewable Energy Systems -- 14.1 Introduction -- 14.2 Forecasting Reserve Using SVM Algorithm -- 14.3 Results. 14.3.1 Training and Data Analysis -- 14.4 Conclusion -- References -- 15 Efficiency Improvement of PV Panel Using PCM Cooling Technique -- 15.1 Introduction -- 15.2 PCM Cooling Technique -- 15.3 Results and Discussion -- 15.4 Conclusion -- References -- 16 Parametric Identification Algorithm Using Chebyshev-Laguerre Functions -- 16.1 Introduction -- 16.2 Synthesis of Orthonormal Chebyshev-Laguerre Functions -- 16.3 Simulation Using Transformed Generalized Orthonormal Chebyshev-Laguerre Functions -- 16.4 Conclusion -- References -- 17 Analysis of Piezoelectric Energy Harvesting Schemes and a Proposition for State-of-the-Art Approach in Hydro-Electric Power Generation -- 17.1 Introduction -- 17.2 Rudiments of Sustainable Piezoelectric Energy Harvesting -- 17.3 Power Harvester Model and Simulation -- 17.3.1 Simulink Model for Power Harvesting Circuitry -- 17.3.2 Flowchart of the Presented Work -- 17.3.3 Test System and Results of Piezoelctric Energy Harvester -- 17.4 A Novel Approach to a Sustainable Piezoelectric Harvester -- 17.5 Conclusion and Future Work -- References -- Author Index. |
| Record Nr. | UNINA-9910743365003321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Smart structures in energy infrastructure : proceedings of ICRTE 2021 / / edited by Anita Khosla and Monika Aggarwal
| Smart structures in energy infrastructure : proceedings of ICRTE 2021 / / edited by Anita Khosla and Monika Aggarwal |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (214 pages) |
| Disciplina | 628 |
| Collana | Studies in Infrastructure and Control |
| Soggetto topico |
Artificial intelligence
Renewable energy sources Computational intelligence |
| ISBN |
981-16-4743-7
981-16-4744-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743391903321 |
| Gateway East, Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||