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Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Pubbl/distr/stampa Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Descrizione fisica 1 online resource (384 pages)
Disciplina 621.317
Collana Artificial Intelligence and Soft Computing for Industrial Transformation
Soggetto topico Artificial intelligence - Industrial applications
Electric power supplies to apparatus - Energy conservation - Data processing
Soggetto genere / forma Electronic books.
ISBN 1-5231-4332-0
1-119-76178-6
1-119-76177-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Design of Low Power Junction Less Double-Gate MOSFET -- 1.1 Introduction -- 1.2 MOSFET Performance Parameters -- 1.3 Comparison of Existing MOSFET Architectures -- 1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) -- 1.5 Heavily Doped JL-DG MOSFET for Biomedical Application -- 1.6 Conclusion -- References -- 2 VLSI Implementation of Vedic Multiplier -- 2.1 Introduction -- 2.2 8x8 Vedic Multiplier -- 2.3 The Architecture of 8x8 Vedic Multiplier (VM) -- 2.3.1 Compressor Architecture -- 2.4 Results and Discussion -- 2.4.1 Instance Power -- 2.4.2 Net Power -- 2.4.3 8-Bit Multiplier -- 2.4.4 16-Bit Multiplier -- 2.4.5 Applications of Multiplier -- 2.5 Conclusion -- References -- 3 Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers -- 3.1 Introduction -- 3.1.1 IOT-Based Sewer Gas Detection -- 3.1.2 Objective -- 3.1.3 Contribution of this Chapter -- 3.1.4 Outline of the Chapter -- 3.2 Related Works -- 3.2.1 Sewer Gas Leakage Detection -- 3.2.2 Crack Detection -- 3.3 Methodology -- 3.3.1 Sewer Gas Detection -- 3.3.2 Crack Detection -- 3.3.3 Experimental Setup -- 3.4 Experimental Results -- 3.5 Conclusion -- References -- 4 Machine Learning for Smart Healthcare Energy-Efficient System -- 4.1 Introduction -- 4.1.1 IoT in the Digital Age -- 4.1.2 Using IoT to Enhance Healthcare Services -- 4.1.3 Edge Computing -- 4.1.4 Machine Learning -- 4.1.5 Application in Healthcare -- 4.2 Related Works -- 4.3 Edge Computing -- 4.3.1 Architecture -- 4.3.2 Advantages of Edge Computing over Cloud Computing -- 4.3.3 Applications of Edge Computing in Healthcare -- 4.3.4 Edge Computing Advantages -- 4.3.5 Challenges -- 4.4 Smart Healthcare System -- 4.4.1 Methodology -- 4.4.2 Data Acquisition and IoT End Device.
4.4.3 IoT End Device and Backend Server -- 4.5 Conclusion and Future Directions -- References -- 5 Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices -- 5.1 Introduction -- 5.2 Types of Attacks -- 5.3 Some Countermeasures for the Attacks -- 5.4 Machine Learning Solutions -- 5.5 Machine Learning Algorithms -- 5.6 Authentication Process Based on Machine Learning -- 5.7 Internet of Things (IoT) -- 5.8 IoT-Based Attacks -- 5.8.1 Botnets -- 5.8.2 Man-in-the-Middle -- 5.9 Information and Identity Theft -- 5.10 Social Engineering -- 5.11 Denial of Service -- 5.12 Concerns -- 5.13 Conclusion -- References -- 6 Smart Energy-Efficient Techniques for Large-Scale Process Industries -- 6.1 Pumps Operation -- 6.1.1 Parts in a Centrifugal Pump -- 6.1.2 Pump Efficiency -- 6.1.3 VFD -- 6.1.4 VFD and Pump Motor -- 6.1.5 Large HT Motors -- 6.1.6 Smart Pumps -- 6.2 Vapour Absorption Refrigeration System -- 6.2.1 Vapour Compression Refrigeration -- 6.2.2 Vapour Absorption Refrigeration -- 6.3 Heat Recovery Equipment -- 6.3.1 Case Study -- 6.3.2 Advantages of Heat Recovery -- 6.4 Lighting System -- 6.4.1 Technical Terms -- 6.4.2 Introduction -- 6.4.3 LED Lighting -- 6.4.4 Energy-Efficiency Techniques -- 6.4.5 Light Control with IoT -- 6.4.6 EU Practices -- 6.5 Air Conditioners -- 6.5.1 Technical Terms -- 6.5.2 Types of Air Conditioners -- 6.5.3 Star Rating of BEE -- 6.5.4 EU Practices -- 6.5.5 Energy-Efficiency Tips -- 6.5.6 Inverter Air Conditioners -- 6.5.7 IoT-Based Air Conditioners -- 6.6 Fans and Other Smart Appliances -- 6.6.1 BLDC Fan Motors -- 6.6.2 Star Ratings -- 6.6.3 Group Drive of Fans -- 6.6.4 Other Smart Appliances -- 6.7 Motors -- 6.7.1 Motor Efficiency -- 6.7.2 Underrated Operation -- 6.7.3 Energy-Efficient Motors -- 6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors.
6.7.5 Other Salient Points -- 6.7.6 Use of Star-Delta Starter Motor -- 6.8 Energy-Efficient Transformers -- 6.8.1 IEC Recommendation -- 6.8.2 Super Conducting Transformers -- References -- 7 Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network -- 7.1 Introduction -- 7.2 Related Work -- 7.2.1 Existing Techniques -- 7.3 Proposed K-Means Clustering Algorithm -- 7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms -- 7.3.2 Dynamic and Static Clustering -- 7.3.3 Flow Diagram -- 7.3.4 Objective Function -- 7.4 System Model and Assumption -- 7.4.1 Simulation Parameters -- 7.5 Results and Discussion -- 7.6 Conclusions -- References -- 8 Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications -- 8.1 Introduction -- 8.2 PV Panel as Energy Source -- 8.2.1 Solar Cell -- 8.3 Multi-Level Inverter Topologies -- 8.3.1 Types of Inverters Used for Drives -- 8.3.2 Multi-Level Inverters -- 8.4 Experimental Results and Discussion -- 8.4.1 PV Powered H Bridge Inverter-Fed Drive -- 8.4.2 PV Powered DCMLI Fed Drive -- 8.5 Conclusion and Future Scope -- References -- 9 Analysis and Design of Bidirectional Circuits for Energy Storage Application -- 9.1 Introduction -- 9.2 Modes of Operation Based on Main Converters -- 9.2.1 Single-Stage Rectification -- 9.2.2 Single-Stage Inversion -- 9.2.3 Double-Stage Rectification -- 9.2.4 Double-Stage Inversion -- 9.3 Proposed Methodology for Three-Phase System -- 9.3.1 Control Block of Overall System -- 9.3.2 Proposed Carrier-Based PWM Strategy -- 9.3.3 Experiment Results -- 9.4 Conclusion -- References -- 10 Low-Power IOT-Enabled Energy Systems -- 10.1 Overview -- 10.1.1 Conceptions -- 10.1.2 Motivation -- 10.1.3 Methodology -- 10.2 Empowering Tools -- 10.2.1 Sensing Components -- 10.2.2 Movers -- 10.2.3 Telecommunication Technology.
10.2.4 Internet of Things Information and Evaluation -- 10.3 Internet of Things within Power Region -- 10.3.1 Internet of Things along with Vitality Production -- 10.3.2 Smart Metropolises -- 10.3.3 Intelligent Lattice Network -- 10.3.4 Smart Buildings Structures -- 10.3.5 Powerful Usage of Vitality in Production -- 10.3.6 Insightful Transport -- 10.4 Difficulties Relating Internet of Things -- 10.4.1 Vitality Ingestion -- 10.4.2 Synchronization via Internet of Things through Sub-Units -- 10.4.3 Client Confidentiality -- 10.4.4 Safety Challenges -- 10.4.5 IoT Standardization and Architectural Concept -- 10.5 Upcoming Developments -- 10.5.1 IoT and Block Chain -- 10.5.2 Artificial Intelligence and IoT -- 10.5.3 Green IoT -- 10.6 Conclusion -- References -- 11 Efficient Renewable Energy Systems -- Introduction -- 11.1 Renewable-Based Available Technologies -- 11.1.1 Wind Power -- 11.1.2 Solar Power -- 11.1.3 Tidal Energy -- 11.1.4 Battery Storage System -- 11.1.5 Solid Oxide Energy Units for Enhancing Power Life -- 11.2 Adaptability Frameworks -- 11.2.1 Distributed Energy Resources (DER) -- 11.2.2 New Age Grid Connection -- 11.3 Conclusion -- References -- 12 Efficient Renewable Energy Systems -- 12.1 Introduction -- 12.1.1 World Energy Scenario -- 12.2 Sources of Energy: Classification -- 12.3 Renewable Energy Systems -- 12.3.1 Solar Energy -- 12.3.2 Wind -- 12.3.3 Geothermal -- 12.3.4 Biomass -- 12.3.5 Ocean -- 12.3.6 Hydrogen -- 12.4 Solar Energy -- 12.5 Wind Energy -- 12.6 Geothermal Energy -- 12.7 Biomass -- 12.7.1 Forms of Biomass -- 12.8 Ocean Power -- 12.9 Hydrogen -- 12.10 Hydro Power -- 12.11 Conclusion -- References -- 13 Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management -- 13.1 Introduction -- 13.1.1 Novelty of the Work -- 13.1.2 Benefit to Society -- 13.2 Development of the Proposed System.
13.3 System Description -- 13.3.1 Study of the Crop Under Experiment -- 13.3.2 Hardware of the System -- 13.3.3 Software of the System -- 13.4 Layers of the System Architecture -- 13.4.1 Application Layer -- 13.4.2 Cloud Layer -- 13.4.3 Network Layer -- 13.4.4 Physical Layer -- 13.5 Calibration -- 13.6 Layout of the Sprinkler System -- 13.7 Testing -- 13.8 Results and Discussion -- 13.9 Conclusion -- References -- 14 A Behaviour-Based Authentication to Internet of Things Using Machine Learning -- 14.1 Introduction -- 14.2 Basics of Internet of Things (IoT) -- 14.2.1 The IoT Reference Model -- 14.2.2 Working of IoT -- 14.2.3 Utilization of Internet of Things (IoT) -- 14.3 Authentication in IoT -- 14.3.1 Methods of Authentication -- 14.4 User Authentication Based on Behavioral-Biometric -- 14.4.1 Machine Learning -- 14.4.2 Machine Learning Algorithms -- 14.5 Threats and Challenges in the Current Security Solution for IoT -- 14.6 Proposed Methodology -- 14.6.1 Collection of Gait Dataset -- 14.6.2 Gait Data Preprocessing -- 14.6.3 Reduction in Data Size -- 14.6.4 Gaits Feature -- 14.6.5 Classification -- 14.7 Conclusion and Future Work -- References -- 15 A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas -- 15.1 Introduction -- 15.2 Proposed System -- 15.2.1 Problem Statement -- 15.2.2 Overview -- 15.2.3 System Components -- 15.3 Work Process -- 15.3.1 System Hardware -- 15.3.2 Connections and Circuitry -- 15.4 Optimization Framework -- 15.4.1 Fuzzy Goal Description -- 15.4.2 Characterizing Fuzzy Membership Function -- 15.4.3 Construction of FGP Model -- 15.4.4 Definition of Variables and Parameters -- 15.4.5 Fuzzy Goal Description -- 15.5 Creation of Database and Website -- 15.5.1 Hosting PHP Application and Creation of MySQL Database -- 15.5.2 Creation of API (Application Programming Interfaces) Key.
15.6 Libraries Used and Code Snipped.
Record Nr. UNINA-9910555117803321
Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Pubbl/distr/stampa Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Descrizione fisica 1 online resource (384 pages)
Disciplina 621.317
Collana Artificial Intelligence and Soft Computing for Industrial Transformation
Soggetto topico Artificial intelligence - Industrial applications
Electric power supplies to apparatus - Energy conservation - Data processing
ISBN 1-5231-4332-0
1-119-76178-6
1-119-76177-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Design of Low Power Junction Less Double-Gate MOSFET -- 1.1 Introduction -- 1.2 MOSFET Performance Parameters -- 1.3 Comparison of Existing MOSFET Architectures -- 1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) -- 1.5 Heavily Doped JL-DG MOSFET for Biomedical Application -- 1.6 Conclusion -- References -- 2 VLSI Implementation of Vedic Multiplier -- 2.1 Introduction -- 2.2 8x8 Vedic Multiplier -- 2.3 The Architecture of 8x8 Vedic Multiplier (VM) -- 2.3.1 Compressor Architecture -- 2.4 Results and Discussion -- 2.4.1 Instance Power -- 2.4.2 Net Power -- 2.4.3 8-Bit Multiplier -- 2.4.4 16-Bit Multiplier -- 2.4.5 Applications of Multiplier -- 2.5 Conclusion -- References -- 3 Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers -- 3.1 Introduction -- 3.1.1 IOT-Based Sewer Gas Detection -- 3.1.2 Objective -- 3.1.3 Contribution of this Chapter -- 3.1.4 Outline of the Chapter -- 3.2 Related Works -- 3.2.1 Sewer Gas Leakage Detection -- 3.2.2 Crack Detection -- 3.3 Methodology -- 3.3.1 Sewer Gas Detection -- 3.3.2 Crack Detection -- 3.3.3 Experimental Setup -- 3.4 Experimental Results -- 3.5 Conclusion -- References -- 4 Machine Learning for Smart Healthcare Energy-Efficient System -- 4.1 Introduction -- 4.1.1 IoT in the Digital Age -- 4.1.2 Using IoT to Enhance Healthcare Services -- 4.1.3 Edge Computing -- 4.1.4 Machine Learning -- 4.1.5 Application in Healthcare -- 4.2 Related Works -- 4.3 Edge Computing -- 4.3.1 Architecture -- 4.3.2 Advantages of Edge Computing over Cloud Computing -- 4.3.3 Applications of Edge Computing in Healthcare -- 4.3.4 Edge Computing Advantages -- 4.3.5 Challenges -- 4.4 Smart Healthcare System -- 4.4.1 Methodology -- 4.4.2 Data Acquisition and IoT End Device.
4.4.3 IoT End Device and Backend Server -- 4.5 Conclusion and Future Directions -- References -- 5 Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices -- 5.1 Introduction -- 5.2 Types of Attacks -- 5.3 Some Countermeasures for the Attacks -- 5.4 Machine Learning Solutions -- 5.5 Machine Learning Algorithms -- 5.6 Authentication Process Based on Machine Learning -- 5.7 Internet of Things (IoT) -- 5.8 IoT-Based Attacks -- 5.8.1 Botnets -- 5.8.2 Man-in-the-Middle -- 5.9 Information and Identity Theft -- 5.10 Social Engineering -- 5.11 Denial of Service -- 5.12 Concerns -- 5.13 Conclusion -- References -- 6 Smart Energy-Efficient Techniques for Large-Scale Process Industries -- 6.1 Pumps Operation -- 6.1.1 Parts in a Centrifugal Pump -- 6.1.2 Pump Efficiency -- 6.1.3 VFD -- 6.1.4 VFD and Pump Motor -- 6.1.5 Large HT Motors -- 6.1.6 Smart Pumps -- 6.2 Vapour Absorption Refrigeration System -- 6.2.1 Vapour Compression Refrigeration -- 6.2.2 Vapour Absorption Refrigeration -- 6.3 Heat Recovery Equipment -- 6.3.1 Case Study -- 6.3.2 Advantages of Heat Recovery -- 6.4 Lighting System -- 6.4.1 Technical Terms -- 6.4.2 Introduction -- 6.4.3 LED Lighting -- 6.4.4 Energy-Efficiency Techniques -- 6.4.5 Light Control with IoT -- 6.4.6 EU Practices -- 6.5 Air Conditioners -- 6.5.1 Technical Terms -- 6.5.2 Types of Air Conditioners -- 6.5.3 Star Rating of BEE -- 6.5.4 EU Practices -- 6.5.5 Energy-Efficiency Tips -- 6.5.6 Inverter Air Conditioners -- 6.5.7 IoT-Based Air Conditioners -- 6.6 Fans and Other Smart Appliances -- 6.6.1 BLDC Fan Motors -- 6.6.2 Star Ratings -- 6.6.3 Group Drive of Fans -- 6.6.4 Other Smart Appliances -- 6.7 Motors -- 6.7.1 Motor Efficiency -- 6.7.2 Underrated Operation -- 6.7.3 Energy-Efficient Motors -- 6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors.
6.7.5 Other Salient Points -- 6.7.6 Use of Star-Delta Starter Motor -- 6.8 Energy-Efficient Transformers -- 6.8.1 IEC Recommendation -- 6.8.2 Super Conducting Transformers -- References -- 7 Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network -- 7.1 Introduction -- 7.2 Related Work -- 7.2.1 Existing Techniques -- 7.3 Proposed K-Means Clustering Algorithm -- 7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms -- 7.3.2 Dynamic and Static Clustering -- 7.3.3 Flow Diagram -- 7.3.4 Objective Function -- 7.4 System Model and Assumption -- 7.4.1 Simulation Parameters -- 7.5 Results and Discussion -- 7.6 Conclusions -- References -- 8 Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications -- 8.1 Introduction -- 8.2 PV Panel as Energy Source -- 8.2.1 Solar Cell -- 8.3 Multi-Level Inverter Topologies -- 8.3.1 Types of Inverters Used for Drives -- 8.3.2 Multi-Level Inverters -- 8.4 Experimental Results and Discussion -- 8.4.1 PV Powered H Bridge Inverter-Fed Drive -- 8.4.2 PV Powered DCMLI Fed Drive -- 8.5 Conclusion and Future Scope -- References -- 9 Analysis and Design of Bidirectional Circuits for Energy Storage Application -- 9.1 Introduction -- 9.2 Modes of Operation Based on Main Converters -- 9.2.1 Single-Stage Rectification -- 9.2.2 Single-Stage Inversion -- 9.2.3 Double-Stage Rectification -- 9.2.4 Double-Stage Inversion -- 9.3 Proposed Methodology for Three-Phase System -- 9.3.1 Control Block of Overall System -- 9.3.2 Proposed Carrier-Based PWM Strategy -- 9.3.3 Experiment Results -- 9.4 Conclusion -- References -- 10 Low-Power IOT-Enabled Energy Systems -- 10.1 Overview -- 10.1.1 Conceptions -- 10.1.2 Motivation -- 10.1.3 Methodology -- 10.2 Empowering Tools -- 10.2.1 Sensing Components -- 10.2.2 Movers -- 10.2.3 Telecommunication Technology.
10.2.4 Internet of Things Information and Evaluation -- 10.3 Internet of Things within Power Region -- 10.3.1 Internet of Things along with Vitality Production -- 10.3.2 Smart Metropolises -- 10.3.3 Intelligent Lattice Network -- 10.3.4 Smart Buildings Structures -- 10.3.5 Powerful Usage of Vitality in Production -- 10.3.6 Insightful Transport -- 10.4 Difficulties Relating Internet of Things -- 10.4.1 Vitality Ingestion -- 10.4.2 Synchronization via Internet of Things through Sub-Units -- 10.4.3 Client Confidentiality -- 10.4.4 Safety Challenges -- 10.4.5 IoT Standardization and Architectural Concept -- 10.5 Upcoming Developments -- 10.5.1 IoT and Block Chain -- 10.5.2 Artificial Intelligence and IoT -- 10.5.3 Green IoT -- 10.6 Conclusion -- References -- 11 Efficient Renewable Energy Systems -- Introduction -- 11.1 Renewable-Based Available Technologies -- 11.1.1 Wind Power -- 11.1.2 Solar Power -- 11.1.3 Tidal Energy -- 11.1.4 Battery Storage System -- 11.1.5 Solid Oxide Energy Units for Enhancing Power Life -- 11.2 Adaptability Frameworks -- 11.2.1 Distributed Energy Resources (DER) -- 11.2.2 New Age Grid Connection -- 11.3 Conclusion -- References -- 12 Efficient Renewable Energy Systems -- 12.1 Introduction -- 12.1.1 World Energy Scenario -- 12.2 Sources of Energy: Classification -- 12.3 Renewable Energy Systems -- 12.3.1 Solar Energy -- 12.3.2 Wind -- 12.3.3 Geothermal -- 12.3.4 Biomass -- 12.3.5 Ocean -- 12.3.6 Hydrogen -- 12.4 Solar Energy -- 12.5 Wind Energy -- 12.6 Geothermal Energy -- 12.7 Biomass -- 12.7.1 Forms of Biomass -- 12.8 Ocean Power -- 12.9 Hydrogen -- 12.10 Hydro Power -- 12.11 Conclusion -- References -- 13 Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management -- 13.1 Introduction -- 13.1.1 Novelty of the Work -- 13.1.2 Benefit to Society -- 13.2 Development of the Proposed System.
13.3 System Description -- 13.3.1 Study of the Crop Under Experiment -- 13.3.2 Hardware of the System -- 13.3.3 Software of the System -- 13.4 Layers of the System Architecture -- 13.4.1 Application Layer -- 13.4.2 Cloud Layer -- 13.4.3 Network Layer -- 13.4.4 Physical Layer -- 13.5 Calibration -- 13.6 Layout of the Sprinkler System -- 13.7 Testing -- 13.8 Results and Discussion -- 13.9 Conclusion -- References -- 14 A Behaviour-Based Authentication to Internet of Things Using Machine Learning -- 14.1 Introduction -- 14.2 Basics of Internet of Things (IoT) -- 14.2.1 The IoT Reference Model -- 14.2.2 Working of IoT -- 14.2.3 Utilization of Internet of Things (IoT) -- 14.3 Authentication in IoT -- 14.3.1 Methods of Authentication -- 14.4 User Authentication Based on Behavioral-Biometric -- 14.4.1 Machine Learning -- 14.4.2 Machine Learning Algorithms -- 14.5 Threats and Challenges in the Current Security Solution for IoT -- 14.6 Proposed Methodology -- 14.6.1 Collection of Gait Dataset -- 14.6.2 Gait Data Preprocessing -- 14.6.3 Reduction in Data Size -- 14.6.4 Gaits Feature -- 14.6.5 Classification -- 14.7 Conclusion and Future Work -- References -- 15 A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas -- 15.1 Introduction -- 15.2 Proposed System -- 15.2.1 Problem Statement -- 15.2.2 Overview -- 15.2.3 System Components -- 15.3 Work Process -- 15.3.1 System Hardware -- 15.3.2 Connections and Circuitry -- 15.4 Optimization Framework -- 15.4.1 Fuzzy Goal Description -- 15.4.2 Characterizing Fuzzy Membership Function -- 15.4.3 Construction of FGP Model -- 15.4.4 Definition of Variables and Parameters -- 15.4.5 Fuzzy Goal Description -- 15.5 Creation of Database and Website -- 15.5.1 Hosting PHP Application and Creation of MySQL Database -- 15.5.2 Creation of API (Application Programming Interfaces) Key.
15.6 Libraries Used and Code Snipped.
Record Nr. UNINA-9910830773703321
Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui