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Advances in Data Science and Analytics : Concepts and Paradigms
| Advances in Data Science and Analytics : Concepts and Paradigms |
| Autore | Niranjanamurthy M |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2022 |
| Descrizione fisica | 1 online resource (353 pages) |
| Altri autori (Persone) |
GianeyHemant Kumar
GandomiAmir H |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-79282-7
1-119-79281-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910623984703321 |
Niranjanamurthy M
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| Newark : , : John Wiley & Sons, Incorporated, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Automation and Computational Intelligence for Road Maintenance and Management : Advances and Applications
| Automation and Computational Intelligence for Road Maintenance and Management : Advances and Applications |
| Autore | Zakeri Hamzeh |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2022 |
| Descrizione fisica | 1 online resource (547 pages) |
| Altri autori (Persone) |
NejadFereidoon Moghadas
GandomiAmir H |
| ISBN |
1-119-80067-6
1-119-80065-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Dedication -- Preface -- Author Biography -- Chapter 1 Concepts and Foundations Automation and Emerging Technologies -- 1.1 Introduction -- 1.2 Structure and Framework of Automation and Key Performance Indexes (KPIs) -- 1.3 Advanced Image Processing Techniques -- 1.4 Fuzzy and Its Recent Advances -- 1.5 Automatic Detection and Its Applications in Infrastructure -- 1.6 Feature Extraction and Fragmentation Methods -- 1.7 Feature Prioritization and Selection Methods -- 1.8 Classification Methods and Its Applications in Infrastructure Management -- 1.9 Models of Performance Measures and Quantification in Automation -- 1.10 Nature-Inspired Optimization Algorithms (NIOAS) -- 1.11 Summary and Conclusion -- 1.12 Questions and Exercise -- Chapter 2 The Structure and Framework of Automation and Key Performance Indices (KPIs) -- 2.1 Introduction -- 2.2 Macro Plan and Architecture of Automation -- 2.2.1 Infrastructure Automation -- 2.2.2 Importance of Infrastructure Automation Evaluation -- 2.3 A General Framework and Design of Automation -- 2.4 Infrastructure Condition Index and Its Relationship with Cracking -- 2.4.1 Road Condition Index -- 2.4.2 Bridge Condition Index -- 2.4.3 Tunnel Condition Index -- 2.5 Automation, Emerging Technologies, and Futures Studies -- 2.6 Summary and Conclusion -- 2.7 Questions -- Further Reading -- Chapter 3 Advanced Images Processing Techniques -- Introduction -- 3.1 Preprocessing (PPS) -- 3.1.1 Edge Preservation Index (EPI) -- 3.1.2 Edge-Strength Similarity-Based Image Quality Metric (ESSIM) -- 3.1.3 QILV Index -- 3.1.4 Structural Content Index (SCI) -- 3.1.5 Signal-To-Noise Ratio Index (PSNR) -- 3.1.6 Computational time index (CTI) -- 3.2 Preprocessing Using Single-Level Methods -- 3.2.1 Single-Level Methods -- 3.2.2 Linear Location Filter (LLF) -- 3.2.3 Median Filter.
3.2.4 Wiener Filter -- 3.3 Preprocessing Using Multilevel (Multiresolution) Methods -- 3.3.1 Wavelet Method -- 3.3.2 Ridgelet Transform -- 3.3.3 Curvelet Transform -- 3.3.4 Decompaction and Reconstruction Images Using Shearlet Transform (SHT) -- 3.3.5 Discrete Shearlet Transform (DST) -- 3.3.6 Shearlet Decompaction and Reconstruction -- 3.3.7 Shearlet and Wavelet Comparison -- 3.3.8 Complex Shearlet Transform -- 3.3.9 Complex Shearlet Transform for Image Enhancement -- 3.3.10 Low and High frequencies of Complex Shearlet Transform for Image Denoising -- 3.4 General Comparison of Single/Multilevel Methods and Selection of Methods for Noise Removal and Image Enhancement -- 3.5 Application of Preprocessing -- 3.5.1 Pavement Surface Drainage Condition Assessment -- 3.6 Summary and Conclusion -- 3.7 Questions and Exercises -- Chapter 4 Fuzzy and Its Recent Advances -- 4.1 Introduction -- 4.1.1 Type-1 Fuzzy Set Theory -- 4.1.2 Type-2 Fuzzy Set Theory -- 4.1.3 a-Plane Representation of General Type-2 Fuzzy Sets -- 4.1.4 Type-Reduction -- 4.1.5 Defuzzification -- 4.1.6 Type-3 Fuzzy Logic Sets -- 4.2 Ambiguity Modeling in the Fuzzy Methods -- 4.2.1 Background of General Type-2 Fuzzy Sets -- 4.3 Theory of Automatic Methods for MF Generation -- 4.3.1 Automatic Procedure to Generate a 3D Membership Function -- 4.4 Steps and Components of General 3D Type-2 Fuzzy Logic Systems (G3DT2 FL) -- 4.4.1 General 3D Type-2 Fuzzy Logic Systems (G3DT2 FL) -- 4.5 General 3D Type-2 Polar Fuzzy Method -- 4.5.1 Automatic MF Generator -- 4.5.2 A Measure of Ultrafuzziness -- 4.5.3 Theoretic Operations of 3D Type-2 Fuzzy Sets in the Polar Frame -- 4.5.4 Representation of Fuzzy 3D Polar Rules -- 4.5.5 ϑ-Slice and α − Planes -- 4.6 Computational Performance (CP) -- 4.7 Application of G3DT2FLS in Pattern Recognition. 4.7.1 Examples of the Application of Fuzzy Methods in Infrastructure Management -- 4.8 Summary and Conclusion -- 4.9 Questions and Exercises -- Further Reading -- Chapter 5 Automatic Detection and Its Applications in Infrastructure -- 5.1 Introduction -- 5.1.1 Photometric Hypotheses (PH) -- 5.1.2 Geometric and Photometric Hypotheses (GPH) -- 5.1.3 Geometric Hypotheses (GH) -- 5.1.4 Transform Hypotheses (TH) -- 5.2 The Framework for Automatic Detection of Abnormalities in Infrastructure Images -- 5.2.1 Wavelet Method -- 5.2.2 High Amplitude Wavelet Coefficient Percentage (HAWCP) -- 5.2.3 High-Frequency Wavelet Energy Percentage (HFWEP) -- 5.2.4 Wavelet Standard Deviation (WSTD) -- 5.2.5 Moments of Wavelet -- 5.2.6 High Amplitude Shearlet Coefficient Percentage (HASHCP) -- 5.2.7 High-Frequency Shearlet Energy Percentage (HFSHEP) -- 5.2.8 Fractal Index -- 5.2.9 Moments of Complex Shearlet -- 5.2.10 Central Moments q -- 5.2.11 Hu Moments -- 5.2.12 Bamieh Moments -- 5.2.13 Zernike Moments -- 5.2.14 Statistic of Complex Shearlet -- 5.2.15 Contrast of Complex Shearlet -- 5.2.16 Correlation of Complex Shearlet -- 5.2.17 Uniformity of Complex Shearlet -- 5.2.18 Homogeneity of Complex Shearlet -- 5.2.19 Entropy of Complex Shearlet -- 5.2.20 Local Standard Deviation of Complex Shearlet Index (F_Local_STD) -- 5.3 Summary and Conclusion -- 5.4 Questions and Exercises -- Further Reading -- Chapter 6 Feature Extraction and Fragmentation Methods -- 6.1 Introduction -- 6.2 Low-Level Feature Extraction Methods -- 6.3 Shape-Based Feature (SBF) -- 6.3.1 Center of Gravity (COG) or Center of Area (COA) -- 6.3.2 Axis of Least Inertia (ALI) -- 6.3.3 Average Bending Energy -- 6.3.4 Eccentricity Index (ECI) -- 6.3.5 Circularity Ratio (CIR) -- 6.3.6 Ellipse Variance Feature (EVF) -- 6.3.7 Rectangularity Feature (REF) -- 6.3.8 Convexity Feature (COF). 6.3.9 Euler Number Feature (ENF) -- 6.3.10 Profiles Feature (PRF) -- 6.4 1D Function-Based Features for Shape Representation -- 6.4.1 Complex Coordinates Feature (CCF) -- 6.4.2 Extracting Edge Characteristics Using Complex Coordinates -- 6.4.3 Edge Detection Using Even and Odd Shearlet Symmetric Generators -- 6.4.4 Object Detection and Isolation Using the Shearlet Coefficient Feature (SCF) -- 6.5 Polygonal-Based Features (PBF) -- 6.6 Spatial Interrelation Feature (SIF) -- 6.7 Moments Features (MFE) -- 6.8 Scale Space Approaches for Feature Extraction (SSA) -- 6.9 Shape Transform Features (STF) -- 6.9.1 Radon Transform Features (RTF) -- 6.9.2 Linear Radon Transform -- 6.9.3 Translation of RT -- 6.9.4 Scaling of RT -- 6.9.5 Point and Line Transform Using RT -- 6.9.6 RT in Sparse Objects -- 6.9.7 Point and Line in RT -- 6.10 Various Case-Based Examples in Infrastructures Management -- 6.10.1 Case 1: Feature Extraction from Polypropylene Modified Bitumen Optical Microscopy Images -- 6.10.2 Ratio of Number of Black Pixels to the Number of Total Pixels (RBT) -- 6.10.3 Ratio of Number of Black Pixels to the Number of Total Pixels in Watershed Segmentation (RWS) -- 6.10.4 Number and Average Area of the White Circular Objects in the Binary Image (The number of circular objects [NCO] & -- ACO) -- 6.10.5 Entropy of the Image -- 6.10.6 Radon Transform Maximum Value (RTMV) -- 6.10.7 Entropy of Radon Transform (ERT) -- 6.10.8 High Amplitude Radon Percentage (HARP) -- 6.10.9 High-Energy Radon Percentage (HERP) -- 6.10.10 Standard Deviation of Radon Transform (STDR) -- 6.10.11 Qth-Moment of Radon Transform (QMRT) -- 6.10.12 Case 2: Image-Based Feature Extraction for Pavement Skid Evaluation -- 6.10.13 Case 3: Image-Based Feature Extraction for Pavement Texture Drainage Capability Evaluation. 6.10.14 Case 4: Image-Based Features Extraction in Pavement Cracking Evaluation -- 6.10.15 Automatic Extraction of Crack Features -- 6.10.16 Extraction of Crack Skeleton Using Shearlet Complex Method -- 6.10.17 Calculate Crack Width Feature Using External Multiplication Method -- 6.10.18 Detection of Crack Starting Feature (Crack Core) Using EPA Emperor Penguin Metaheuristic Algorithm -- 6.10.19 Selection of Crack Root Feature Based on Geodetic Distance -- 6.10.20 Determining Coordinates of the Crack Core as the Optimal Center at the Failure Level using EPA Method -- 6.10.21 Development of New Features for Crack Evaluation Based on Graph Energy -- 6.10.22 Crack Homogeneity Feature Based on Graph Energy Theory -- 6.10.23 Spall Type 1 Feature: Crack Based on Graph Energy Theory in Crack Width Mode -- 6.10.24 General Crack Index Based on Graph Energy Theory -- 6.11 Summary and Conclusion -- 6.12 Questions and Exercises -- Further Reading -- Chapter 7 Feature Prioritization and Selection Methods -- 7.1 Introduction -- 7.2 A Variety of Features Selection Methods -- 7.2.1 Filter Methods -- 7.2.2 Correlation Criteria -- 7.2.3 Mutual Information (MI) -- 7.2.4 Wrapper Methods -- 7.2.5 Sequential Feature Selection (SFS) Algorithm -- 7.2.6 Heuristic Search Algorithm (HAS) -- 7.2.7 Embedded Methods -- 7.2.8 Hybrid Methods -- 7.2.9 Feature Selection Using the Fuzzy Entropy Method -- 7.2.10 Hybrid-Based Feature Selection Using the Hierarchical Fuzzy Entropy Method -- 7.2.11 Step 1: Measure Similarity Index and Evaluate Features -- 7.2.12 Step 2: Final Feature Vector -- 7.3 Classification Algorithm Based on Modified Support Vectors for Feature Selection - CDFESVM -- 7.3.1 Methods for Determining the Fuzzy Membership Function in Feature Selection -- 7.4 Summary and Conclusion -- 7.5Questions and Exercises -- Further Reading. Chapter 8 Classification Methods and Its Applications in Infrastructure Management. |
| Record Nr. | UNINA-9910580257303321 |
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Zakeri Hamzeh
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| Newark : , : John Wiley & Sons, Incorporated, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Science and Applications : Proceedings of ICDSA 2023, Volume 3
| Data Science and Applications : Proceedings of ICDSA 2023, Volume 3 |
| Autore | Nanda Satyasai Jagannath |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (596 pages) |
| Altri autori (Persone) |
YadavRajendra Prasad
GandomiAmir H SaraswatMukesh |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9978-17-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- PV Array System Stimulation Affected by Variability in Temperature and Location -- 1 Introduction -- 2 Phtotvoltaic Systems -- 3 System Description -- 3.1 Boost Converter -- 3.2 Inverter -- 3.3 Boost Converter Control Scheme -- 3.4 Inverter Control Scheme -- 4 Conclusion -- References -- A Real-Time Cataract Detection and Diagnosis Through Web-Based Imaging Analysis -- 1 Introduction -- 2 Literature Survey -- 3 Existing System -- 4 Proposed System -- 5 Dataset Details -- 6 Experimental Setup -- 7 Methodology -- 8 Algorithms Used -- 9 Results and Discussions -- 10 Performance Metrics -- 11 Comparative Analysis -- 12 Conclusion -- References -- A Survey of Decentralized Digital Voting System Using Blockchain Technology -- 1 Introduction -- 2 Elements of Voting Systems -- 3 Centralized Voting Technologies -- 3.1 SMS-Based Smartphone Application -- 3.2 Secure Voting Using Biometrics -- 3.3 Authenticated Web-Based Voting -- 3.4 Technologies Used in Constructing E-Voting System -- 4 Blockchain -- 4.1 Smart Contracts -- 4.2 Transactions -- 4.3 Role of Ethereum -- 5 Decentralized E-Voting Systems Overview -- 5.1 Quantum Blockchain -- 5.2 E-Voting with Blockchain -- 5.3 Verify-Your-Vote -- 5.4 E-voting Based on Blockchain and Blind Signature -- 5.5 Privacy Preserving Protocol -- 5.6 Large Scale Election Using Blockchain and Ring Signature -- 5.7 Existing Working Organizations -- 6 Challenges -- 6.1 Challenges of Blockchain -- 6.2 Scalability -- 6.3 Immatureness -- 6.4 Acceptance -- 6.5 Coercion -- 6.6 Energy Efficiency -- 6.7 Governmental Authority Opposition -- 6.8 Security Requirements -- 6.9 Open Issues -- 7 Conclusions -- References -- Multiple Infectious Disease Diagnosis and Detection Using Advanced CNN Models -- 1 Introduction -- 1.1 Paper Structure -- 2 Literature Survey -- 3 Methodology.
3.1 Dataset -- 3.2 Preprocessing -- 3.3 Applied Models -- 3.4 Performance Metrics -- 4 Results -- 5 Conclusion -- References -- Development of Indoor Autonomous Mobile BOT for Static Obstacle Avoidance -- 1 Introduction -- 2 AutoBOT Hardware -- 2.1 NodeMCU ESP12E Module -- 2.2 Ultrasonic Sensor -- 2.3 Infrared Sensor -- 2.4 L298N Driver Module -- 3 AutoBOT Software -- 4 Environment -- 5 Control Interface -- 6 Data Collection and Hardware Results -- 7 Conclusion -- References -- Forest Fire Detection and Prediction Using HSV and MLP -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 4 Technology -- 5 Dataset, Testing and Experiments -- 6 Results and Future Work -- 7 Conclusion -- References -- An Insight into Recent Advances in the Intelligent Controller Methods -- 1 Introduction -- 1.1 Fractional-Order PID Controller (FOPIDC) -- 2 Intelligent Control -- 2.1 Characteristics, Challenges, and Application of Intelligent Control System -- 3 Evolution in Intelligent Controller -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Some Observations on Social Media Mining tools for Health Applications -- 1 Introduction -- 2 Social Media Mining for Health Applications (SMM4HA) -- 3 Issues and Challenges -- 4 Observations of Various Methods Used for SMM4HA -- 5 Conclusion -- References -- Smart Contact Lenses for Monitoring Patient's Vision: A Generic Review -- 1 Introduction -- 2 Why Do Cataracts Occur? And Its Surgery -- 3 How the Eyes Function -- 4 Human Eye Lens -- 5 Related Work -- 5.1 Screen Reader -- 5.2 Braille Displays -- 5.3 Text-to-Speech (TTS) Software -- 5.4 Navigation Aids -- 5.5 Optical Character Recognition (OCR) Software -- 5.6 Voice Assistants -- 6 Recommendation -- 7 Conclusion -- References -- Liver Lesion Detection from MR T1 In-Phase and Out-Phase Fused Images and CT Images Using YOLOv8. 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Setup and Results -- 4.1 Experimental Environment -- 4.2 Dataset -- 4.3 Performance Metrics -- 4.4 Experimental Setup -- 4.5 Results -- 5 Conclusion -- References -- Analyzing Blockchain Data to Detect Bitcoin Addresses Involved in Illicit Activities Using Anomaly Detection -- 1 Introduction -- 2 Literature Review -- 3 Experimental Set up and Algorithm Used -- 3.1 HPCC Systems Architecture -- 3.2 R and R Studio -- 3.3 Algorithm Used: K-Means Clustering -- 4 Methodology -- 4.1 Parser -- 4.2 Feature Extraction -- 4.3 Clustering and Analysis -- 5 Discussion of Results -- 6 Conclusion and Future Scope -- References -- Comparing Spring Boot and ReactJS with Other Web Development Frameworks: A Study -- 1 Introduction -- 1.1 History -- 1.2 Need of Study -- 1.3 Overview -- 2 Review of Literature -- 3 Methodology -- 4 Result -- 5 Discussion -- 6 Conclusion -- References -- Performance Analysis of InceptionV3, VGG16, and Resnet50 Models for Crevices Recognition on Surfaces -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Understanding the Dataset -- 3.2 Data Preprocessing -- 3.3 Designing Model for Crack Detection Using Resnet50, VGG16, and InceptionV3 -- 3.4 Training of Models -- 3.5 Testing of Models -- 4 Results and Discussion -- 5 Conclusion -- References -- A Machine Learning Approach for Moderating Toxic Hinglish Comments of YouTube Videos -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset Collection and Visualization -- 3.2 Text Preprocessing -- 3.3 Model Creation -- 4 Results and Discussion -- 5 Open Challenges -- 5.1 Collecting a Larger Dataset of Hinglish Toxic Comments -- 5.2 Capturing the Contextual and Cultural Nuances of Hinglish Text -- 5.3 Utilizing More Advanced NLP and Machine Learning Techniques. 5.4 Mitigating Human Biases in the Manual Annotation -- 6 Conclusion -- References -- Instant Accident Detection and Emergency Alert System -- 1 Introduction -- 2 Related Work -- 3 Existing System -- 4 Proposed System -- 5 Methodology -- 5.1 Authentication Module -- 5.2 Detection Module -- 5.3 Alert Module -- 6 Results and Discussion -- 7 Conclusion -- References -- A Novel Approach to Video Summarization Using AI-GPT and Speech Recognition -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 4 Result -- 5 Discussion/Future Works -- 6 Conclusion -- References -- Classification of Underwater Fish Species Using Custom-Built Deep Learning Architectures -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Feature Extraction -- 3.2 Classification -- 3.3 Data Set -- 3.4 Data Pre-processing -- 3.5 Splitting the Data Set -- 3.6 Training the Model -- 3.7 Testing the Model -- 4 Architecture -- 4.1 Vgg16 -- 4.2 MobileNetV2 -- 4.3 ResNet50 -- 5 Results -- 5.1 Predictions -- 5.2 Graphs -- 5.3 Confusion Matrix -- 6 Conclusion -- 7 Future Enhancements -- References -- Deep Learning-Based Approach for Plant Disease Classification -- 1 Introduction -- 2 Literature Survey -- 3 Working Flow of the Model -- 4 Proposed Architecture for Neural Network -- 5 Implementation and Result Analysis -- 6 Conclusions -- References -- Prediction of Liver Disease Using Machine Learning Algorithms -- 1 Introduction -- 2 Literature Survey -- 3 Dataset Description -- 4 Proposed Methodology -- 4.1 Data Preprocessing -- 4.2 Label Encoding -- 4.3 Pearson Correlation Coefficient-Based Feature Selection (PCC-FS) -- 4.4 Oversampling -- 4.5 Feature Scaling -- 4.6 Classification -- 4.7 Evaluation Measures -- 5 Results -- 6 Conclusion -- References -- Analysis of Detection of Glioma by Segmentation of Brain Tumor MRI Images Using Deep Learning -- 1 Introduction. 2 Techniques for Segmenting Brain Tumor Images -- 2.1 Manual Segmentation Methods -- 2.2 Semi-Automatic Segmentation Methods -- 2.3 Fully Automatic Segmentation Methods -- 3 Challenges in Fully Automatic Segmentation Methods -- 4 Dataset -- 5 Deep Learning Methods -- 6 Conclusions -- References -- CloneAI: A Deep Learning-Based Approach for Cloned Voice Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset Employed -- 3.2 Pre-processing and Feature Extraction -- 3.3 Model Implementation -- 4 Results and Discussion -- 5 Conclusion -- References -- Analyzing the Performance and Wireless Network Capacity of NOMA: Study of the Impact of OMA and NOMA on 5G Network -- 1 Introduction -- 2 System Model -- 3 Literature Survey -- 4 Compared Analysis -- 5 Conclusion -- References -- Malaria Parasite Detection Using Deep Neural Networks -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Model Training and Classification -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- IoT-Based Agriculture: Identification and Classification of Apple Quality Using Deep Learning -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Problem Statement -- 3.2 Proposed Methodology -- 4 Results Analysis -- 5 Conclusion -- References -- Plant Disease Detection on Edge Devices -- 1 Introduction -- 2 Literature Review -- 3 Dataset -- 4 Deep Learning Models -- 4.1 Comparison Between Model Sizes -- 4.2 Framework -- 5 Raspberry Pi Implementation -- 5.1 Integrated Gradients -- 6 Results -- 6.1 Raspberry Pi's Performance -- 7 Conclusion -- References -- Analyze the Quality of Wine Based on Machine Learning Approach -- 1 Introduction -- 2 Literature Survey -- 3 Quality Prediction Model -- 4 Results and Analysis -- 5 Conclusion -- References. Safeguarding Financial Transaction with Cryptocurrency. |
| Record Nr. | UNINA-9910805579003321 |
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Nanda Satyasai Jagannath
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Science and Applications : Proceedings of ICDSA 2023, Volume 1
| Data Science and Applications : Proceedings of ICDSA 2023, Volume 1 |
| Autore | Nanda Satyasai Jagannath |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (569 pages) |
| Disciplina | 005.7 |
| Altri autori (Persone) |
YadavRajendra Prasad
GandomiAmir H SaraswatMukesh |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9978-62-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Climate Change Parameter Dataset (CCPD): A Benchmark Dataset for Climate Change Parameters in Jammu and Kashmir -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 Overview -- 3.2 Forest Cover -- 3.3 Water Bodies -- 3.4 Agriculture and Vegetation -- 3.5 Population -- 3.6 Temperature -- 3.7 Construction -- 3.8 Air Index -- 4 Dataset Results -- 5 Conclusion -- References -- Brain Tumor Classification Using Deep Learning Techniques -- 1 Introduction -- 2 Review of Previous Work -- 3 Information About the Data and Environmental Setup -- 3.1 Data Preparation and Exploration -- 4 Convolutional Neural Networks and Techniques Implemented -- 4.1 AlexNetV2 -- 4.2 VGG-16 -- 4.3 ResNet-50 -- 4.4 Inception-ResNet -- 4.5 MobileNetv2 -- 5 Experimental Approaches -- 5.1 Novel CNN Architecture -- 5.2 Parallel Networks Model -- 5.3 Machine Learning Assisted -- 6 Optimisation Using Nature-Inspired Algorithms -- 6.1 Particle Swarm Optimization -- 6.2 Genetic Algorithm -- 7 Conclusion -- References -- Machine Learning-Based Hardware Trojans Detection in Integrated Circuits: A Systematic Review -- 1 Introduction -- 2 Machine Learning and Models -- 3 A Review of Machine Learning Methods for Hardware Trojan Detection -- 3.1 Reverse Engineering -- 3.2 Circuit Feature Analysis -- 3.3 Side-Channel Analysis -- 3.4 Golden Model Free Analysis -- 3.5 Classification Approaches -- 3.6 Final Result of Hardware Trojan Detection Approaches -- 4 Discussion and Future Work -- 5 Conclusion -- References -- Impact of Technostress on Employee Retention and Employee Turnover -- 1 Introduction -- 2 Literature Review -- 3 Theoretical Background and Hypothesis -- 4 Methodology -- 5 Data Analysis and Discussion -- 6 Limitations and Future Scope -- 7 Conclusion -- References.
Single Image Dehazing Using DCP with Varying Scattering Constant -- 1 Introduction -- 2 Haze Formation Model -- 3 Solution Approach -- 3.1 Estimation of Atmospheric Light Using DCP -- 3.2 Estimating Omega -- 4 Results and Discussion -- 5 Conclusion -- References -- Detecting IoT Malware Using Federated Learning -- 1 Introduction -- 2 Related Works -- 2.1 Signature-Based Detection -- 2.2 Behavior-Based Detection -- 2.3 Machine Learning-Based Detection -- 2.4 Deep Learning-Based Detection -- 2.5 Motivation for Federated Learning -- 3 Federated Learning -- 3.1 Overview of Federated Learning -- 3.2 Mathematical Formulation -- 3.3 Challenges and Considerations in Federated Learning -- 4 Federated Learning Strategy for IoT Malware Recognition -- 4.1 Obstacles and Rationale -- 4.2 Model Design -- 4.3 Procedure of Federated Learning -- 5 Experimental Results and Evaluation -- 6 Conclusion -- References -- A Deep Learning Approach for BGP Security Improvement -- 1 Introduction -- 2 Related Work -- 3 Deep Learning Models -- 3.1 Convolutional Neural Network (CNN) -- 4 Dataset -- 5 Proposed Technique -- 6 Evaluation Metrics -- 7 Experimental Results -- 8 Conclusion -- References -- Wireless Sensor Network Protocols in Underwater Communication -- 1 Introduction -- 1.1 Underwater Wireless Sensor Network Architecture -- 2 Challenges Regarding UWSNs -- 2.1 Propagation Delay -- 2.2 Bandwidth -- 2.3 Energy Consumption -- 2.4 Communication Coverage -- 2.5 Attenuation -- 2.6 Cost -- 2.7 Sophisticated Techniques -- 3 Routing Protocols -- 3.1 Localization-Based Protocols -- 3.2 Localization-Free Protocols -- 3.3 Cooperation Routing -- 4 Conclusion -- References -- A Genetic Algorithm Approach for Portfolio Optimization -- 1 Introduction -- 1.1 Techniques for Portfolio Optimization -- 2 Genetic Algorithm -- 3 Scope of Genetic Algorithm -- 4 Fitness Function. 5 Genetic Algorithm-Based Portfolio Optimization -- 6 Result and Analysis -- 7 Advantages -- 8 Conclusion -- References -- Security Issues and Solutions in Post Quantum Authenticated Key Exchange for Mobile Devices -- 1 Introduction -- 2 Contribution -- 3 Description of Signal Leakage Attack -- 4 Preliminaries -- 5 Dabra et al. ``Lattice-Based Key Exchange for Mobile Devices ch10dabra2020lba'' -- 6 Statement of Problem -- 6.1 Registration Issues -- 6.2 Password Change Issues -- 6.3 Insider Attack -- 6.4 Signal Leakage Attack -- 7 Changes Required in Dabra et al.'s Registration Phase -- 8 Conclusion/Future Directions -- References -- Towards Decentralized Fog Computing: A Comprehensive Review of Models, Architectures, and Services -- 1 Introduction -- 1.1 Fog Computing, an Extension of Cloud Computing -- 1.2 Fog Over Cloud -- 1.3 Transition from Cloud to Fog -- 2 Motivation -- 3 Literature Survey -- 4 Architectural Model -- 4.1 Architectural Styles -- 4.2 Views -- 4.3 Dimensions -- 4.4 Related Work -- 5 Discussion -- 6 Research Contributions -- 7 Conclusion -- References -- Analysis of Various Mac Protocols in 802.11 AX -- 1 Introduction -- 1.1 OFDMA Multi-user Transmissions in 802.11ax -- 2 Literature Review -- 2.1 Comparison Table -- 3 Conclusion -- References -- Monkeypox Disease Classification Using HOG-SVM Model -- 1 Introduction -- 1.1 Transmission -- 1.2 Symptoms of Monkeypox Disease -- 1.3 Traditional Detection -- 1.4 Traditional Treatments of Monkeypox -- 1.5 AI-Based Detection -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Feature Extraction -- 3.3 Classification -- 3.4 Support Vector Machine (SVM) -- 4 Implementation -- 5 Evaluation Matrices -- 6 Result -- 7 Conclusion -- References -- A Deep Learning Model for Automatic Recognition of Facial Expressions Using Haar Cascade Images -- 1 Introduction. 2 Literature Review -- 3 The Presented Approach -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 Presented Deep Learning Model -- 3.4 Testing -- 4 Result -- 5 Conclusion and Future Work -- References -- Sensing Performance Analysis Using Choatic Signal-Based SCMA Codebook for Secure Cognitive Communication System in 5G -- 1 Introduction -- 1.1 Related Work -- 2 SCMA with Chaotic Sequence-Based System Analysis -- 2.1 Dynamic Characteristic of Chaotic Sequence -- 2.2 SCMA Modeling -- 3 System Model -- 3.1 SCMA Encoding -- 3.2 SCMA Decoding -- 4 Proposed Detection Method -- 4.1 Binary Hypothesis Testing -- 4.2 Wald Hypothesis Test -- 4.3 Weight Assignment Method -- 4.4 Experimental Setup -- 5 Detection Performance Analysis -- 6 Conclusion -- References -- Identification of Severity Level for Diabetic Retinopathy Detection Using Neural Networks -- 1 Introduction -- 2 Review of Literature -- 3 Motivation of Proposed Research Work -- 4 Existing Datasets -- 4.1 Dataset from Zenodo -- 4.2 EyePACS Dataset from Kaggle -- 4.3 APTOS Dataset from Kaggle -- 5 Proposed Methodology -- 5.1 Flow of the Proposed Work -- 5.2 Preprocessing on the Dataset -- 5.3 Architecture Used for the Proposed Work -- 5.4 Implementation Platform and Performance Matrix -- 6 Results -- 7 Conclusion -- 8 Future Work -- References -- Metaheuristic Optimized BiLSTM Univariate Time Series Forecasting of Gold Prices -- 1 Introduction -- 2 Related Works -- 2.1 BiLSTM Overview -- 2.2 Variation Mode Decomposition -- 2.3 Metaheuristics Optimization -- 3 Methods -- 3.1 Overview of Basic Moth Flame Optimizer Algorithm -- 3.2 Modified MFO -- 4 Experiments and Discussion -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Improvised Neural Machine Translation Model for Hinglish to English -- 1 Introduction -- 2 Literature Review. 2.1 Sequence-to-Sequence (STS) -- 2.2 Attention (ATT) Model -- 3 Methodology -- 3.1 Dataset -- 3.2 Processing Data -- 3.3 Proposed System -- 4 Results -- 5 Discussion -- 5.1 No Smoothing -- 5.2 Laplace Smoothing -- 5.3 Additive Smoothing -- 5.4 Exponential Smoothing -- 5.5 Chen and Cherry Smoothing -- 6 Conclusion -- References -- Recording of Class Attendance Using DL-Based Face Recognition Method -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 3.1 Dataset Creation -- 3.2 Preprocessing -- 3.3 Face Detection and Recognition -- 3.4 Attendance Marking and Report Generation -- 3.5 Implementation -- 4 Result Analysis -- 5 Conclusions -- References -- Machine Learning Enabled Hairstyle Recommender System Using Multilayer Perceptron -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Facial Landmark Detection -- 3.4 Face Shape Classification -- 3.5 Model Comparison -- 3.6 Recommendation -- 4 Results and Discussion -- 5 Conclusion -- References -- Automated Health Insurance Management Framework with Intelligent Fraud Detection, Premium Prediction, and Risk Prediction -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Dataset Specifics -- 3.2 Exploratory Data Analysis -- 3.3 Feature Engineering and Selection -- 3.4 Machine Learning Models -- 4 Experimental Results and Discussion -- 5 Conclusion and Future Work -- References -- Responsible Artificial Intelligence for Music Recommendation -- 1 Introduction -- 2 Background and Motivation -- 3 Literature Review -- 3.1 Identifying Research Gaps in the Literature -- 3.2 Contributions of This Paper -- 4 Methodology -- 4.1 Data Acquiring and EDA -- 4.2 Model Development and Evaluation -- 4.3 Feature Importance and Model Retrain -- 4.4 Explainable AI -- 5 Results -- 6 Conclusion -- 7 Future Work -- References. A Robot Mapping Technique for Indoor Environments. |
| Record Nr. | UNINA-9910838288103321 |
|
Nanda Satyasai Jagannath
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Science and Applications : Proceedings of ICDSA 2023, Volume 2
| Data Science and Applications : Proceedings of ICDSA 2023, Volume 2 |
| Autore | Nanda Satyasai Jagannath |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (533 pages) |
| Disciplina | 005.7 |
| Altri autori (Persone) |
YadavRajendra Prasad
GandomiAmir H SaraswatMukesh |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9978-20-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Comparative Analysis of Various SRAM Bit Cells for 32 nm Technology Node -- 1 Introduction -- 2 Review of Pre-existing Cells -- 3 Stability Analysis -- 3.1 Hold Static Noise Margin (HSNM) -- 3.2 Read Static Noise Margin (RSNM) -- 3.3 Write Margin (WM) -- 4 Half Select Disturbance -- 5 Conclusion -- References -- Uncovering the Threat: Exploring Covert Channel Attacks Via Audio Files in Android Applications -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Conclusion -- References -- Emotion Recognition Through Facial Expressions from Images Using Deep Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Model -- 3.1 Face Detection -- 3.2 Image Preprocessing -- 3.3 Feature Extraction -- 3.4 Emotion Classification -- 4 Experimental Results -- 4.1 Dataset -- 4.2 Experimental Results -- 5 Conclusion -- References -- Optimization of Process Parameters in the Abrasive Waterjet Machining Using Bees Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Solution Development -- 4.1 Model or Prototype Solution -- 5 The Mathematical Model -- 5.1 Solution Development -- 5.2 Data Processing -- 6 Validation and Result Analysis -- 6.1 Experimental Design -- 6.2 Result Illustration and Explanation -- 6.3 Validation of the BA Result -- 6.4 Result Analysis -- 7 Conclusion -- References -- Advancement on Steganography: A Review -- 1 Introduction -- 2 Background -- 3 Understanding Various Techniques and Methodologies -- 3.1 Spatial Domain Techniques -- 3.2 Frequency Domain Techniques -- 4 Literature Review -- 5 Possible Problems Faced -- 6 Conclusion -- References -- Ethereum Blockchain for Private Equity Crowdfunding: Enabling Seamless USDC and Share Token Transactions -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Methodology -- 5 Results.
6 Conclusion -- References -- Graph Convolutional Neural Network for IC50 Prediction Model Using Amyotrophic Lateral Sclerosis Targets -- 1 Introduction -- 2 Dataset Formulation -- 3 Model Building -- 4 Results and Discussion -- 5 Conclusion -- References -- Cardiovascular Disease Prediction Using Deep Learning Models -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Data Pre-processing and Cleaning Method -- 3.2 Regularization Technique -- 4 Results -- 5 Conclusions -- 6 Future Scope -- References -- Classification of Skin Cancer Using Integrated Methodology -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Set -- 3.2 Model Implementation and Training -- 4 Results and Analysis -- 5 Conclusion -- References -- Identification of Mycobacterium Tuberculosis Employing VGG-16 Feature Extraction and Classification Using Prominent Machine Learning Classifiers on X-rays -- 1 Introduction -- 2 Literature Review -- 3 Material and Methods -- 3.1 Dataset and Preprocessing -- 3.2 Feature Extraction -- 3.3 ML Classifiers -- 3.4 Performance Metrics -- 4 Results and Discussion -- 5 Conclusion -- References -- Cybercrime Analysis of India Using Machine Learning -- 1 Introduction -- 2 Literature Survey -- 3 Dataset Description -- 3.1 Cybercrimes -- 3.2 Cybercrimes Types -- 3.3 Cybercrimes Motives -- 4 Methodology -- 4.1 Data Preprocessing -- 4.2 Approach -- 4.3 System Architecture -- 5 Results and Analysis -- 5.1 Cybercrimes -- 5.2 Cybercrime Types -- 5.3 Cybercrimes Motives -- 6 Conclusion -- References -- Mapping a Conceptual Model of Colour Forecasting: A Review of Machine Learning Algorithms for Enhanced Prediction Accuracy and Efficiency -- 1 Background -- 1.1 The Era of Digital Colour Forecasting -- 2 Significance of Colour Trend Forecasting -- 2.1 The Colour Cycle -- 2.2 Process of Colour Forecasting. 3 Science Meets Intuition -- 3.1 Big Data for Colour Forecasting -- 3.2 Artificial Intelligence Techniques for Colour Trend Forecasting -- 3.3 Databases -- 3.4 Applications of Machine Learning in Colour Identification Process -- 4 Colour System and Colour Spaces -- 4.1 Pantone Colour System -- 5 Discussion -- 6 Conclusion -- References -- Estimation of Net Primary Productivity Using CASA Biosphere Model in Hyderabad and Roorkee Region of India -- 1 Introduction -- 2 Literature Review -- 3 Study Area -- 4 Dataset Used for Analysis -- 4.1 Soil Data -- 4.2 Vegetation Data -- 4.3 Land Use Data -- 5 Model Structure -- 6 Results -- 6.1 NPP Variation within a Year -- 6.2 NPP Variation Over the Years -- 7 Conclusion -- References -- Machine Learning Models for Chronic Renal Disease Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Preprocessing: Handling Missing Value -- 3.2 Data Preprocessing: Feature Selection -- 3.3 Model Training -- 3.4 Model Evaluation and Selection -- 4 Discussion -- 5 Conclusion and Future Work -- References -- ARTHRO-Knee Osteoarthritis Detection Using Deep Learning -- 1 Introduction -- 2 Related Survey -- 3 Material and Methods -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Convolutional Neural Networks -- 4 Proposed Method -- 5 Results and Discussion -- 6 Conclusion -- References -- Improvised Real-Time Tweet Analysis for Brand Recognition -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Method -- 4 Result and Discussion -- 5 Conclusion -- References -- AI-Based Facial Emotion Recognition -- 1 Introduction -- 2 Related Work -- 3 Simulation Setup -- 3.1 Background -- 3.2 Dataset, Preprocessing, and Augmentation -- 3.3 Improved VGG16 Architecture -- 3.4 Tuning -- 4 Results -- 5 Observations -- 6 Conclusion -- References. Improved Genetic Algorithm in a Static Environment for the Robotic Path Planning Problem -- 1 Introduction -- 2 Description of the Optimization Problem -- 2.1 Robotic Path Planning Problem -- 2.2 Genetic Algorithm -- 2.3 Genetic Algorithm in Path Planning -- 2.4 Problem Model -- 2.5 Optimization Method -- 3 Optimization Framework and Test Cases -- 4 Results -- 5 Conclusion and Outlook -- References -- Development of An Event-Based Dataset For Abnormal Activity Detection -- 1 Introduction -- 2 Related Works -- 2.1 Machine Learning Using Event Camera Datasets -- 2.2 Methodology -- 3 Experiments -- 3.1 Event Dataset for Abnormal Activity Detection -- 3.2 Clustering on Event Dataset -- 4 Future Work and Conclusion -- References -- Media Text Analysis Based on One-Dimensional Hashtag Embeddings -- 1 Introduction -- 2 Notation and Problem Definition -- 3 Methodology -- 4 Empirical Results -- 4.1 Dataset Description -- 4.2 One-Dimensional Embedding -- 5 Conclusion -- References -- Occluded Face Recognition Using Non-Global Features Extraction and K-Means Clustering Algorithm -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Image Preprocessing -- 3.2 Features Extraction -- 3.3 Classifiers -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Results -- 5 Conclusion -- References -- Brain Tumor Segmentation Using Gaussian-Based U-Net Architecture -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 BraTS Dataset -- 3.2 Pre-processing -- 3.3 U-Net Architecture -- 3.4 Model Training -- 3.5 Model Evaluation Metrics -- 3.6 Numerical Result and Discussion -- 3.7 Merits and Contrast -- 4 Conclusion and Future Work -- References -- Utility of Smoothing Techniques in Yield Curve Modeling for Non-Steady State Data of Sri Lanka Capital Market -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Experiment -- 5 Results -- 6 Discussion. 7 Conclusion -- References -- WSN-Based Secure and Energy-Efficient Smart Parking Management System (SPMS) Using FFA-ANN -- 1 Introduction -- 2 Motivation of Research -- 3 Related Work -- 4 Problem Definition -- 5 Proposed Work -- 6 Result and Discussions -- 6.1 Network Throughput -- 6.2 Number of Alive Nodes -- 7 Conclusion -- References -- Multilingual Approach to Decode Shree Rama Prashanavali Using Character Recognition and String Matching -- 1 Introduction -- 2 Literature and Survey -- 3 Methodology -- 3.1 Algorithm for the Proposed Work -- 4 Results and Discussions -- 5 Conclusion -- References -- An Enhanced Approach for Automatic Sound Event Detection Using Neural Networks -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Data Set -- 3.2 Feature Extraction -- 3.3 Model Implementation -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- Detecting Issues Related to Environmental, Social, and Corporate Governance Using SEC-BERT -- 1 Introduction -- 2 Related Works -- 3 Problem Statement -- 4 Dataset -- 5 Methodology -- 6 Experiments and Results -- 7 ESG Issue Detector (EID) Tool -- 8 Conclusion -- References -- Comprehensive Analysis of Deep Learning Models for Brain Tumor Detection from Medical Imaging -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 AlexNet -- 3.2 VGG-16 [12] -- 3.3 ResNet50 -- 3.4 DenseNet-121 -- 3.5 GoogleNet -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Experiments and Result Analysis -- 5 Conclusion -- References -- Face Counting Based on Pre-trained Machine Learning Models: A Brief Systematic Review -- 1 Introduction -- 2 Background Study -- 3 Face Detection Algorithms -- 3.1 Haar Cascade Classifier -- 3.2 Multi-task Cascaded Convolutional Networks (MTCNN) Architecture -- 3.3 RetinaFace Architecture -- 4 Results -- 5 Discussion -- 6 Conclusion -- References. A Machine Learning-Driven Soil Nutrient and Crop Yield Recommendation Platform with Pesticide Suggestions. |
| Record Nr. | UNINA-9910841863303321 |
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Nanda Satyasai Jagannath
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Science and Applications : Proceedings of ICDSA 2023, Volume 4
| Data Science and Applications : Proceedings of ICDSA 2023, Volume 4 |
| Autore | Nanda Satyasai Jagannath |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (546 pages) |
| Disciplina | 005.7 |
| Altri autori (Persone) |
YadavRajendra Prasad
GandomiAmir H SaraswatMukesh |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN |
9789819978144
9789819978137 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910841854503321 |
|
Nanda Satyasai Jagannath
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Handbook of Formal Optimization
| Handbook of Formal Optimization |
| Autore | Kulkarni Anand J |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (1406 pages) |
| Altri autori (Persone) | GandomiAmir H |
| ISBN |
9789819738205
9789819738199 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910874666603321 |
|
Kulkarni Anand J
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Handbook of Genetic Programming Applications / / edited by Amir H. Gandomi, Amir H. Alavi, Conor Ryan
| Handbook of Genetic Programming Applications / / edited by Amir H. Gandomi, Amir H. Alavi, Conor Ryan |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (589 p.) |
| Disciplina | 004 |
| Soggetto topico |
Artificial intelligence
Computational intelligence Artificial Intelligence Computational Intelligence |
| ISBN | 3-319-20883-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Graph-Based Evolutionary Art -- Genetic Programming for Modelling of Geotechnical Engineering Systems -- Application of Genetic Programming in Hydrology -- Application of Gene-Expression Programming in Hydraulics Engineering -- Genetic Programming applications in Chemical Sciences and Engineering -- Application of Genetic Programming for Electrical Engineering Predictive Modeling -- Mate Choice in Evolutionary Computation -- Genetically Improved Software -- Design of Real-Time Computer-Based Systems Using Developmental Genetic Programming -- Image Classification with Genetic Programming -- On the Application of Genetic Programming for New Generation of Ground Motion Prediction Equations -- Evaluation of Liquefaction Potential of Soil Based on Shear Wave Velocity Using Multi-Gene Genetic Programming -- Site Characterization Using GP, MARS, and GPR -- Use of Genetic Programming Based Surrogate Models to Simulate Complex Geochemical Transport Processes in Contaminated Mine Sites -- Potential of Genetic Programming in Hydroclimatic Prediction of Droughts -- Application of Genetic Programming for Uniaxial and Multiaxial Modeling of Concrete -- Genetic Programming for Mining Association Rules in Relational Database Environments -- Evolving GP Classifiers for Streaming Data Tasks with Concept Change and Label Budgets -- A New Evolutionary Approach to Geotechnical and Geo-environmental Modelling -- Application of GFA-MLR and G/PLS Techniques in QSAR/QSPR Studies with Application in Medicinal Chemistry and Predictive Toxicology -- Trading Volitility using Highly Accurate Symbolic Regression -- GPTIPS 2: An Open-Source Software Platform for Symbolic Data Mining -- eCrash: A Genetic Programming-Based Testing Tool for Object-Oriented Software. |
| Record Nr. | UNINA-9910299214103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of International Conference on Data Science and Applications : ICDSA 2021, Volume 1
| Proceedings of International Conference on Data Science and Applications : ICDSA 2021, Volume 1 |
| Autore | Saraswat Mukesh |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2022 |
| Descrizione fisica | 1 online resource (845 pages) |
| Altri autori (Persone) |
RoySarbani
ChowdhuryChandreyee GandomiAmir H |
| Collana | Lecture Notes in Networks and Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9789811651205
9789811651199 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910510554203321 |
|
Saraswat Mukesh
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| Singapore : , : Springer Singapore Pte. Limited, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of International Conference on Data Science and Applications : ICDSA 2021, Volume 2
| Proceedings of International Conference on Data Science and Applications : ICDSA 2021, Volume 2 |
| Autore | Saraswat Mukesh |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (792 pages) |
| Altri autori (Persone) |
RoySarbani
ChowdhuryChandreyee GandomiAmir H |
| Collana | Lecture Notes in Networks and Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9789811653483
9789811653476 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910510564403321 |
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Saraswat Mukesh
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| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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