Neural Networks, Machine Learning, and Image Processing: Mathematical Modeling and Applications
Objektkategorie:
Elektronische Ressource
Person/Institution:
Verlag:
Taylor & Francis Group
Ort:
Milton
Entstehungszeit:
2022
Sprache:
Englisch
Weitere Objektinformationen
Abstract:
The text presents mathematical modeling techniques such as wavelet transform, differential calculus, and numerical techniques for multi-dimensional data. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields such as electrical, electronics and communication, and computer.
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Part I: Mathematical modeling and neural network's mathematical essence -- 1 Mathematical modeling on thermoregulation in sarcopenia -- 1.1 Introduction -- 1.2 Discretization -- 1.3 Modeling and simulation of basal metabolic rate and skin layer thickness -- 1.3.1 Basal metabolic rate model -- 1.3.2 Skin layer thickness model -- 1.4 Mathematical model and boundary conditions -- 1.4.1 Mathematical model -- 1.4.2 Boundary conditions -- 1.4.2.1 Boundary condition at x = 0 (skin surface) -- 1.4.2.2 Boundary condition at x = L[sub(3)] (body core) -- 1.5 Solution of the model -- 1.6 Numerical results and discussion -- 1.6.1 Temperature results -- 1.7 Conclusions -- References -- 2 Multi-objective university course scheduling for uncertainly generated courses -- 2.1 Introduction -- 2.2 Literature review -- 2.3 Formulation of problem -- 2.4 Methodology -- 2.4.1 MOUSPUGC with linear membership function -- 2.4.2 MOUSPUGC with nonlinear membership function -- 2.5 Numerical example -- 2.6 Results and discussion -- 2.7 Conclusions -- References -- 3 MChCNN: a deep learning approach to detect text-based hate speech -- 3.1 Introduction: background and driving forces -- 3.2 Related work -- 3.3 Experiments and results -- 3.3.1 Input layer -- 3.3.2 Embedding layer -- 3.3.3 Convolutional layers -- 3.4 Conclusions -- References -- 4 PSO-based PFC Cuk converter-fed BLDC motor drive for automotive applications -- 4.1 Introduction -- 4.2 Operation of Cuk converter-fed BLDC motor drive system -- 4.3 Controller operation -- 4.4 Results and discussion -- 4.5 Conclusions -- References -- 5 Optimized feature selection for condition-based monitoring of cylindrical bearing using wavelet transform and ANN -- 5.1 Introduction -- 5.2 Methodology.
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Part I: Mathematical modeling and neural network's mathematical essence -- 1 Mathematical modeling on thermoregulation in sarcopenia -- 1.1 Introduction -- 1.2 Discretization -- 1.3 Modeling and simulation of basal metabolic rate and skin layer thickness -- 1.3.1 Basal metabolic rate model -- 1.3.2 Skin layer thickness model -- 1.4 Mathematical model and boundary conditions -- 1.4.1 Mathematical model -- 1.4.2 Boundary conditions -- 1.4.2.1 Boundary condition at x = 0 (skin surface) -- 1.4.2.2 Boundary condition at x = L[sub(3)] (body core) -- 1.5 Solution of the model -- 1.6 Numerical results and discussion -- 1.6.1 Temperature results -- 1.7 Conclusions -- References -- 2 Multi-objective university course scheduling for uncertainly generated courses -- 2.1 Introduction -- 2.2 Literature review -- 2.3 Formulation of problem -- 2.4 Methodology -- 2.4.1 MOUSPUGC with linear membership function -- 2.4.2 MOUSPUGC with nonlinear membership function -- 2.5 Numerical example -- 2.6 Results and discussion -- 2.7 Conclusions -- References -- 3 MChCNN: a deep learning approach to detect text-based hate speech -- 3.1 Introduction: background and driving forces -- 3.2 Related work -- 3.3 Experiments and results -- 3.3.1 Input layer -- 3.3.2 Embedding layer -- 3.3.3 Convolutional layers -- 3.4 Conclusions -- References -- 4 PSO-based PFC Cuk converter-fed BLDC motor drive for automotive applications -- 4.1 Introduction -- 4.2 Operation of Cuk converter-fed BLDC motor drive system -- 4.3 Controller operation -- 4.4 Results and discussion -- 4.5 Conclusions -- References -- 5 Optimized feature selection for condition-based monitoring of cylindrical bearing using wavelet transform and ANN -- 5.1 Introduction -- 5.2 Methodology.
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Datensatz angelegt am:
2023-04-12
Zuletzt geändert am:
2022-11-10
In Portal übernommen am:
2023-04-12
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