Applications of Mathematical Modeling, Machine Learning, and Intelligent Computing for Industrial Development

Applications of Mathematical Modeling, Machine Learning, and Intelligent Computing for Industrial Development PDF

Author: Madhu Jain

Publisher: CRC Press

Published: 2023-06-07

Total Pages: 410

ISBN-13: 1000885607

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The text focuses on mathematical modeling and applications of advanced techniques of machine learning, and artificial intelligence, including artificial neural networks, evolutionary computing, data mining, and fuzzy systems to solve performance and design issues more precisely. Intelligent computing encompasses technologies, algorithms, and models in providing effective and efficient solutions to a wide range of problems, including the airport’s intelligent safety system. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields that include industrial engineering, manufacturing engineering, computer engineering, and mathematics. The book: Discusses mathematical modeling for traffic, sustainable supply chain, vehicular Ad-Hoc networks, and internet of things networks with intelligent gateways Covers advanced machine learning, artificial intelligence, fuzzy systems, evolutionary computing, and data mining techniques for real- world problems Presents applications of mathematical models in chronic diseases such as kidney and coronary artery diseases Highlights advances in mathematical modeling, strength, and benefits of machine learning and artificial intelligence, including driving goals, applicability, algorithms, and processes involved Showcases emerging real-life topics on mathematical models, machine learning, and intelligent computing using an interdisciplinary approach The text presents emerging real-life topics on mathematical models, machine learning, and intelligent computing in a single volume. It will serve as an ideal text for senior undergraduate students, graduate students, and researchers in diverse fields, including industrial and manufacturing engineering, computer engineering, and mathematics.

Applied Mathematics, Modeling and Computer Simulation

Applied Mathematics, Modeling and Computer Simulation PDF

Author: C.-H. Chen

Publisher: IOS Press

Published: 2024-01-19

Total Pages: 1266

ISBN-13: 1643684590

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Applied mathematics, modelling, and computer simulation are central to many aspects of engineering and computer science, and continue to be of intrinsic importance to the development of modern technologies. This book presents the proceedings of AMMCS 2023, the 3rd International Conference on Applied Mathematics, Modeling and Computer Simulation, held on 12 and 13 August 2023 in Wuhan, China. The conference provided an ideal opportunity for scholars and researchers to communicate important recent developments in their areas of specialization to their colleagues, and to scientists in related disciplines. More than 250 submissions were received for the conference, of which 133 were selected for presentation at the conference and inclusion here after a thorough peer-review process. These range from the theoretical and conceptual to strongly pragmatic papers addressing industrial best practice, and cover topics such as mathematical modeling and application; engineering applications and scientific computations; and the simulation of intelligent systems. The book explores practical experiences and enlightening ideas, and will be of interest to researchers, practitioners, and to all those working in the fields of applied mathematics, modeling and computer simulation.

Neural Networks, Machine Learning, and Image Processing

Neural Networks, Machine Learning, and Image Processing PDF

Author: Manoj Sahni

Publisher: CRC Press

Published: 2022-12-15

Total Pages: 221

ISBN-13: 1000814297

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SECTION I Mathematical Modeling and Neural Network’ Mathematical Essence Chapter 1 Mathematical Modeling on Thermoregulation in Sarcopenia 1.1. Introduction 1.2. Discretization 1.3. Modeling and Simulation of Basal Metabolic Rate and Skin Layers Thickness 1.4. Mathematical Model and Boundary Conditions 1.5. Solution of the Model 1.6. Numerical Results and discussion 1.7. Conclusion References Chapter 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 2.5 Numerical Example 2.6 Result and Discussion 2.7 Conclusion References Chapter 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. Experiment and Results 3.4. Conclusion References Chapter 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. Result and Discussion 4.5. Conclusion References Chapter 5 Optimize Feature Selection for Condition based monitoring of Cylindrical bearing using Wavelet transform and ANN 5.1. Introduction 5.2. Methodology 5.3. Data Preparation 5.4. Result and Discussion 5.5. Conclusion References Chapter 6 SafeShop - An integrated system for safe pickup of items during COVID-19 6.1. Introduction 6.2. Literature Survey 6.3. Methodology 6.4. Result and Discussion 6.5. Conclusion References Chapter 7 Solution of First Order Fuzzy Differential Equation using Numerical Method 7.1. Introduction 7.2. Preliminaries 7.3. Methodology 7.4. Illustration 7.5. Conclusion References SECTION II Simulations in Machine Learning and Image Processing Chapter 8 Multi-layer Encryption Algorithm for Data Integrity in Cloud Computing 8.1. Introduction 8.2. Related works 8.3. Algorithm description 8.4. Simulation and performance analysis 8.5. Conclusion and Future Work References Chapter 9 Anomaly detection using class of supervised and unsupervised learning algorithms 9. 1. Introduction 9.2. Adaptive threshold and regression techniques for anomaly detection 9.3. Unsupervised Learning techniques for anomaly detection 9.4. Description of the dataset 9.5 Results and Discussions 9.6. Conclusion References Chapter 10 Improving Support Vector Machine accuracy with Shogun’s multiple kernel learning 10. 1. Introduction 10. 2. Support Vector Machine Statistics 10.3. Experiment and Result 10.4 Conclusion References Chapter 11 An Introduction to Parallelisable String-Based SP-Languages 11.1. Introduction 11.2. Parallelisable string-based SP-languages 11.3. Parallel Regular Expression 11.4. Equivalence of Parallel Regular Expression and Branching Automaton 11.5. Parallelisable String-Based SP-Grammar 11.6. Parallelisable String-Based SP-Parallel Grammar 11.7. Conclusion 11.8. Applications 11.9. Future Scope References Chapter 12 Detection of Disease using Machine Learning 12.1. Introduction 12.2. Techniques Applied 12.3. GENERAL ARCHITECTURE OF AI/ML 12.4. EXPERIMENTAL OUTCOMES 12.5. Conclusion References Chapter 13 Driver Drowsiness Detection Using Eye Tracing System 13.1. Introduction 13.2. Literature Review 13.3. Research Method 13.4. Observations and Results 13.5. Conclusion References Chapter 14 An Efficient Image Encryption Scheme Combining Rubik Cube Principle with Masking 14.1 Introduction 14.2 Preliminary Section 14.3 Proposed Work 14. 4 Experimental Setup and Simulation Analysis 14.5 Conclusion References

Computational Statistical Methodologies and Modeling for Artificial Intelligence

Computational Statistical Methodologies and Modeling for Artificial Intelligence PDF

Author: Priyanka Harjule

Publisher: CRC Press

Published: 2023-03-31

Total Pages: 389

ISBN-13: 1000831078

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This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Engineering Mathematics and Artificial Intelligence

Engineering Mathematics and Artificial Intelligence PDF

Author: Herb Kunze

Publisher: CRC Press

Published: 2023-07-26

Total Pages: 530

ISBN-13: 1000907872

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Explains the theory behind Machine Learning and highlights how Mathematics can be used in Artificial Intelligence Illustrates how to improve existing algorithms by using advanced mathematics and discusses how Machine Learning can support mathematical modeling Captures how to simulate data by means of artificial neural networks and offers cutting-edge Artificial Intelligence technologies Emphasizes the classification of algorithms, optimization methods, and statistical techniques Explores future integration between Machine Learning and complex mathematical techniques

Mathematical Modeling for Intelligent Systems

Mathematical Modeling for Intelligent Systems PDF

Author: Mukesh Kumar Awasthi

Publisher: CRC Press

Published: 2022-07-29

Total Pages: 263

ISBN-13: 1000618404

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Mathematical Modeling for Intelligent Systems: Theory, Methods, and Simulation aims to provide a reference for the applications of mathematical modeling using intelligent techniques in various unique industry problems in the era of Industry 4.0. Providing a thorough introduction to the field of soft-computing techniques, this book covers every major technique in artificial intelligence in a clear and practical style. It also highlights current research and applications, addresses issues encountered in the development of applied systems, and describes a wide range of intelligent systems techniques, including neural networks, fuzzy logic, evolutionary strategy, and genetic algorithms. This book demonstrates concepts through simulation examples and practical experimental results. Key Features: • Offers a well-balanced mathematical analysis of modeling physical systems • Summarizes basic principles in differential geometry and convex analysis as needed • Covers a wide range of industrial and social applications and bridges the gap between core theory and costly experiments through simulations and modeling • Focuses on manifold ranging from stability of fluid flows, nanofluids, drug delivery, and security of image data to pandemic modeling, etc. This book is primarily aimed at advanced undergraduates and postgraduate students studying computer science, mathematics, and statistics. Researchers and professionals will also find this book useful.

Advances in Mathematical and Computational Modeling of Engineering Systems

Advances in Mathematical and Computational Modeling of Engineering Systems PDF

Author: Mukesh Kumar Awasthi

Publisher: CRC Press

Published: 2023-02-20

Total Pages: 361

ISBN-13: 1000838099

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The text covers a wide range of topics such as mathematical modeling of crop pest control management, water resources management, impact of anthropogenic activities on atmospheric carbon dioxide concentrations, impact of climate changes on melting of glaciers and polar bear populations, dynamics of slow–fast predator-prey system and spread and control of HIV epidemic. It emphasizes the use of mathematical modeling to investigate the fluid flow problems including the breaking of viscoelastic jet, instability arising in nanofiber, flow in an annulus channel, and thermal instability in nano-fluids in a comprehensive manner. This book will be a readily accessible source of information for the students, researchers and policymakers interested in the application of mathematical and computational modeling techniques to investigate various biological and engineering phenomena. Features Focuses on the current modeling and computational trends to investigate various ecological, epidemiological, and engineering systems. Presents the mathematical modeling of a wide range of ecological and environmental issues including crop pest control management, water resources management, the effect of anthropogenic activities on atmospheric carbon dioxide concentrations, and impact of climate changes on melting of glaciers and polar bear population. Covers a wide range of topics including the breaking of viscoelastic jet, instability arising in nanofiber, flow in an annulus channel, and thermal instability in nano-fluids. Examines evolutionary models i.e., models of time-varying processes. Highlights the recent developments in the analytical methods to investigate the nonlinear dynamical systems. Showcases diversified applications of computational techniques to solve practical biological and engineering problems. The book focuses on the recent research developments in the mathematical modeling and scientific computing of biological and engineering systems. It will serve as an ideal reference text for senior undergraduate, graduate students, and researchers in diverse fields including ecological engineering, environmental engineering, computer engineering, mechanical engineering, mathematics, and fluid dynamics.

Optimization and Computing Using Intelligent Data-Driven Approaches for Decision-Making

Optimization and Computing Using Intelligent Data-Driven Approaches for Decision-Making PDF

Author: Irfan Ali

Publisher:

Published: 2024-11-20

Total Pages: 0

ISBN-13: 9781032621661

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This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques. It further covers important topics such as the use of machine learning and the internet of things, multi-objective optimization under Hesitant Fermatean Fuzzy and Uncertain environment. This Book: Addresses solving practical problems such as supply chain management, smart manufacturing, and healthcare analytics using intelligent computing and discusses solving the Fuzzy Inference System in Ant Colony Optimization for Travelling Salesman Problems Presents an overview of AI and Explainable AI Decision-Making XAIDM and illustrates a data-driven optimization concept for modelling environmental and economic sustainability. Discusses Machine Learning based Multi Objective Optimization Technique for Load Balancing in Integrated Fog Cloud Environment. Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals. Discusses Sustainable Transit of Hazardous Waste, Green Fractional Transportation System, Perishable Inventory, M-Estimation of Functional Regression Operator and Intuitionistic Fuzzy Sets applications. The text is primarily written for graduate students, and academic researchers in diverse fields including operations research, mathematics, statistics, computer science, information and communication technology and industrial engineering.

Research Directions in Computational Mechanics

Research Directions in Computational Mechanics PDF

Author: National Research Council

Publisher: National Academies Press

Published: 1991-02-01

Total Pages: 145

ISBN-13: 0309046483

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Computational mechanics is a scientific discipline that marries physics, computers, and mathematics to emulate natural physical phenomena. It is a technology that allows scientists to study and predict the performance of various productsâ€"important for research and development in the industrialized world. This book describes current trends and future research directions in computational mechanics in areas where gaps exist in current knowledge and where major advances are crucial to continued technological developments in the United States.

Artificial Intelligence for Cognitive Modeling

Artificial Intelligence for Cognitive Modeling PDF

Author: Pijush Dutta

Publisher: CRC Press

Published: 2023-04-19

Total Pages: 451

ISBN-13: 1000864243

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This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model. Features: A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB) A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS) Formulation of the nonlinear model like analysis of ANOVA and response surface methodology Variety of solved problems on ANOVA and RSM Case studies of above mentioned intelligent techniques on the different process control systems This book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.