Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications, Okwu Modestus O., Tartibu Lagouge K.
Описание: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems.The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
Автор: Oliva Diego, Abd Elaziz Mohamed, Hinojosa Salvador Название: Metaheuristic Algorithms for Image Segmentation: Theory and Applications ISBN: 3030129330 ISBN-13(EAN): 9783030129330 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images.
Автор: by Ali Kaveh; Armin Dadras Eslamlou Название: Metaheuristic Optimization Algorithms in Civil Engineering ISBN: 303045472X ISBN-13(EAN): 9783030454722 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Optimum stacking sequence design of composite laminates for maximum buckling load capacity.- Optimum Design of Castellated Beams with Composite Action and Semi-Rigid Connection.- Optimal Design of Steel Curved Roof Frames by Enhanced Vibrating Particles System Algorithm.- Geometry and sizing optimization of steel pitched roof frames.- Two-Stage Optimal Sensor Placement Using Graph-Theory and Evolutionary Algorithms.- The charged system search algorithm for adaptive node moving refinement in discrete least-squares meshless method.- Performance-based multi-objective optimization of large steel structures.- Optimal Seismic Design of Steel Plate Shear Walls Using CBO and ECBO Algorithms.- Colliding Bodies Optimization Algorithm for Structural Optimization of Offshore Wind Turbines with Frequency Constraints.- Colliding Bodies Optimization for Analysis and Design of Water Distribution Systems.- Optimization of tower crane location and material quantity between supply and demand points.- Optimization of Building Components with SustainabilityAspects in BIM Environment.- Multi-objective optimization of construction site layout.- Multi-objective electrical energy scheduling in smart homes using ant lion optimizer and evidential reasoning
Автор: Diego Oliva; Mohamed Abd Elaziz; Salvador Hinojosa Название: Metaheuristic Algorithms for Image Segmentation: Theory and Applications ISBN: 3030129306 ISBN-13(EAN): 9783030129309 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implemented using various metaheuristics and hybridization techniques leading to a broader understanding of how image segmentation problems can be solved from an optimization perspective. The field of image processing is constantly changing due to the extensive integration of cameras in devices; for example, smart phones and cars now have embedded cameras. The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images. Metaheuristic algorithms have also been used in various fields of science and technology as the demand for new methods designed to solve complex optimization problems increases.
This didactic book is primarily intended for undergraduate and postgraduate students of science, engineering, and computational mathematics. It is also suitable for courses such as artificial intelligence, advanced image processing, and computational intelligence. The material is also useful for researches in the fields of evolutionary computation, artificial intelligence, and image processing.
Описание: Chapter 1. Introduction: Optimization and Metaheuristics Algorithms.- Chapter 2. Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms.- Chapter 3. Tackling Power Quality Issues using Metaheuristics.- Chapter 4. Meta-Heuristic application in Suppression of Noise.- Chapter 5. A review on Genetic Algorithm and its application in Power system Engineering.- Chapter 6. Different Variants of Particle Swarm Optimization Algorithms and its Application: A Review.- Chapter 7. Application of Metaheuristics in Power Electronics.- Chapter 8. Cuckoo Search Algorithm: A Review of Recent Variants and Engineering Applications.- Chapter 9. Energy Management System for Hybrid Energy System: Renewable Integration, modeling & optimization, control aspects and conceptual framework.- Chapter 10. Recent Advances and Application of Metaheuristic Algorithms: A survey (2014-2020).
Описание: (ii) Describing the problem: Diffusion-weighted magnetic resonance imaging (DW-MRI) is used for non-invasive investigations of anatomical connectivity in the human brain, while Q-ball imaging (QBI) is a diffusion MRI reconstruction technique based on the orientation distribution function (ODF), which detects the dominant fiber orientations;
Описание: This book presents a collection of the most recent hybrid methods for image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence.
Описание: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques.
Автор: Jos? Mar?a Ponce-Ortega; Luis Germ?n Hern?ndez-P?r Название: Optimization of Process Flowsheets through Metaheuristic Techniques ISBN: 3030062848 ISBN-13(EAN): 9783030062842 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.
Описание: Preface.- Introduction.- Simulated Annealing.- Optimization by Recurrent Neural Networks.- Genetic Algorithms and Genetic Programming.- Evolutionary Strategies.- Differential Evolution.- Estimation of Distribution Algorithms.- Mimetic Algorithms.- Topics in EAs.- Particle Swarm Optimization.- Artificial Immune Systems.- Ant Colony Optimization.- Tabu Search and Scatter Search.- Bee Metaheuristics.- Harmony Search.- Biomolecular Computing.- Quantum Computing.- Other Heuristics-Inspired Optimization Methods.- Dynamic, Multimodal, and Constraint-Satisfaction Optimizations.- Multiobjective Optimization.- Appendix 1: Discrete Benchmark Functions.- Appendix 2: Test Functions.- Index.
Автор: Fouad Bennis; Rajib Kumar Bhattacharjya Название: Nature-Inspired Methods for Metaheuristics Optimization ISBN: 3030264572 ISBN-13(EAN): 9783030264574 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.
Автор: Kumar Abhishek, Rathore Pramod Singh, Diaz Vicente Garcia Название: Swarm Intelligence Optimization: Algorithms and Applications ISBN: 1119778743 ISBN-13(EAN): 9781119778745 Издательство: Wiley Рейтинг: Цена: 28979.00 р. Наличие на складе: Поставка под заказ.
Описание:
Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.
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