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26 produkter
26 produkter
Handbook of Whale Optimization Algorithm
Variants, Hybrids, Improvements, and Applications
Häftad, Engelska, 2023
1 681 kr
Skickas inom 10-15 vardagar
Handbook of Whale Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides the most in-depth look at an emerging meta-heuristic that has been widely used in both science and industry. Whale Optimization Algorithm has been cited more than 5000 times in Google Scholar, thus solving optimization problems using this algorithm requires addressing a number of challenges including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters to name a few. This handbook provides readers with in-depth analysis of this algorithm and existing methods in the literature to cope with such challenges.
The authors and editors also propose several improvements, variants and hybrids of this algorithm. Several applications are also covered to demonstrate the applicability of methods in this book.
Provides in-depth analysis of equations, mathematical models and mechanisms of the Whale Optimization Algorithm Proposes different variants of the Whale Optimization Algorithm to solve binary, multiobjective, noisy, dynamic and combinatorial optimization problems Demonstrates how to design, develop and test different hybrids of Whale Optimization Algorithm Introduces several application areas of the Whale Optimization Algorithm, focusing on sustainability Includes source code from applications and algorithms that is available online
1 778 kr
Kommande
Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains.It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.Provides comprehensive coverage of advanced intelligence methodsIncludes real-world examples and case studies that illustrate the application of these methods across a wide range of fieldsBegins with an introduction to Deep Learning concepts and quickly moves to the most leading-edge topics in computational intelligence, all with an application to data science techniques
Digital Transformation in the Construction Industry
Sustainability, Resilience, and Data-Centric Engineering
Häftad, Engelska, 2025
3 100 kr
Skickas inom 10-15 vardagar
Digital Transformation in the Construction Industry: Sustainability, Resilience, and Data-Centric Engineering delivers timely and much sought-after guidance related to novel, digital-first practices and the latest technological tools, the gradual adoption of which is being embraced to significantly reshape the way buildings and other infrastructure assets are designed, constructed, operated, and maintained.Methodological and practice-informed investigations by scholars and researchers from across the globe, providing a wealth of knowledge relevant for, and applicable to, different geographical and economic contexts, are coherently collated in this edited volume. This systematic analysis of cutting-edge developments (such as Building Information Modeling, Internet of Things, Artificial Intelligence, Machine Learning, Big Data, Augmented Reality, Virtual Reality, 3D Printing, and Structural Health Monitoring) is accompanied by discussions on challenges and opportunities that digitalization engenders. Additionally, real-word case studies enrich the coverage, highlighting how these innovative solutions can contribute to establishing working efficiencies that can at the same time aid the impactful realization of globally recognized sustainability goals.Readers in both academic and professional settings are, therefore, not only equipped with a comprehensive overview of the state of the art but also offered an insightful reference resource for future works in the area.Covers emerging technologies comprehensivelyEmphasizes the use of digital tools to support achievements for worldwide net zero targetsFocuses on lean and agile construction practices to improve project efficiency and reduce waste
1 781 kr
Kommande
Grey Wolf Optimizer: A Pack of Solutions for Your Optimization Problems offers in-depth coverage of recent theoretical advancements in GWO, as well as several variants, improvements, and hybrid approaches developed to enhance the GWO's performance and adaptability. The use of generative AI to improve this algorithm and make it more generic is also explored, along with diverse applications across multiple fields to illustrate the practical utility and versatility of the methods presented. The book offers a deep dive into the algorithm's foundations and presents new developments to help researchers overcome common challenges.It features numerous case studies and real-world examples across various fields, such as engineering, healthcare, finance, and environmental management. These applications demonstrate the versatility and effectiveness of the GWO in addressing complex, interdisciplinary challenges, making the content highly relevant and practical for readers. Written by some of the world’s most highly cited researchers in the field of artificial intelligence, algorithms, and machine learning, the book serves as an essential resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.Helps readers understand the evolution, strengths, and current standing of the Grey Wolf Optimizer as a powerful optimization techniqueHelps readers grasp the core concepts and theoretical foundations necessary for effective applicationIntroduces novel variants, improvements, and hybrid approaches designed to tackle optimization problems involving binary, multi-objective, noisy, dynamic, and combinatorial challengesFeatures numerous case studies and real-world examples across various fields, such as engineering, healthcare, finance, and environmental management
Advanced Concepts in Grey Wolf Optimizer
Leading the Pack in Advanced Optimization
Häftad, Engelska, 2026
1 981 kr
Kommande
Advanced Concepts in Grey Wolf Optimizer: Leading the Pack in Advanced Optimization provides in-depth coverage of recent theoretical advancements in GWO, as well as advanced methods to handle issues such as multiple objectives, constraints, binary variables, large search spaces, dynamic goals, and uncertain data. This book assumes familiarity with optimization fundamentals and therefore dives directly into multi-objective, constrained, binary, and dynamic-environment variants, as well as GWO-ML/LLM hybrids. Extensive real-world case studies in areas such as energy systems, supply-chain design, LLM fine-tuning, robotics, and finance ensure that both scholars and engineers can translate the material into deployable solutions. The authors present important new theories, hybrids with Machine Learning/Deep Learning, and hybrid methods that increase GWO’s performance. The use of generative AI to improve this algorithm and make it more generic is also explored, along with diverse applications across multiple fields to illustrate the practical utility and versatility of the methods presented. Written by some of the world’s most highly cited researchers in the field of artificial intelligence, algorithms, and machine learning, the book serves as an advanced resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.Presents the use of new AI tools such as Generative AI (GenAI), Large Language Models (LLM), and Data Processing (DP) with the Grey Wolf Optimizer, showing readers how these technologies can improve and expand GWO capabilitiesProvides a comprehensive overview of the latest GWO modifications and hybrid approaches, including methods to handle complex challenges such as multi-objective tasks, constraints, noisy data, and dynamic conditionsIncludes many practical examples and real-world case studies from areas such as engineering, healthcare, finance, and robotics
Handbook of Moth-Flame Optimization Algorithm
Variants, Hybrids, Improvements, and Applications
Inbunden, Engelska, 2022
1 448 kr
Skickas inom 10-15 vardagar
Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.Key Features:Reviews the literature of the Moth-Flame Optimization algorithmProvides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithmProposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problemsDemonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithmIntroduces several applications areas of the Moth-Flame Optimization algorithmThis handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas.
Handbook of Moth-Flame Optimization Algorithm
Variants, Hybrids, Improvements, and Applications
Häftad, Engelska, 2025
666 kr
Skickas inom 10-15 vardagar
Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.Key Features:Reviews the literature of the Moth-Flame Optimization algorithmProvides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithmProposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problemsDemonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithmIntroduces several applications areas of the Moth-Flame Optimization algorithmThis handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas.
Multi-objective Optimization Techniques
Variants, Hybrids, Improvements, and Applications
Inbunden, Engelska, 2025
2 409 kr
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The book establishes how to design, develop, and test different hybrids of multi-objective optimization algorithms. It presents several application areas of multi-objective optimization algorithms.Presents a thorough analysis of equations, mathematical models, and mechanisms of multi-objective optimization algorithms.Explores different alternatives of multi-objective optimization algorithms to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems.Illustrates how to design, develop, and test different hybrids of multi-objective optimization algorithms. Discusses multi-objective optimization techniques for cloud, fog, and edge computing.Highlights applications of multi-objective optimization in diverse sectors such as engineering, e-healthcare, and scheduling.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, communications engineering, computer science and engineering, and mathematics.
1 283 kr
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This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron.
1 071 kr
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This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.
1 071 kr
Skickas inom 10-15 vardagar
This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms.
719 kr
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This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
Advances in Swarm Intelligence
Variations and Adaptations for Optimization Problems
Inbunden, Engelska, 2022
1 650 kr
Skickas inom 10-15 vardagar
Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. The book also includes studies on application domain specific adaptations in the SI techniques.
Advances in Swarm Intelligence
Variations and Adaptations for Optimization Problems
Häftad, Engelska, 2023
1 650 kr
Skickas inom 10-15 vardagar
Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. The book also includes studies on application domain specific adaptations in the SI techniques.
Future Research Directions in Computational Intelligence
Selected Papers from the 3rd EAI International Conference on Computational Intelligence and Communication
Inbunden, Engelska, 2023
2 453 kr
Skickas inom 10-15 vardagar
This book presents select papers from 3rd EAI International Conference on Computational Intelligence and Communications (CICom 2022). The papers reveal recent advances in the broader domains of Computational Intelligence including (1) automation, control, and intelligent transportation system, (2) big data, internet of things, and smart cities, (3) wireless communication systems and cyber security and (4) human/brain-computer interfaces, and image and pattern recognition. The book demonstrates complex real-world problems in which mathematical or traditional modellings are not the preferred solution, hence alternative solutions are needed. This collection of applications demonstrates the important advances in computational intelligence. The book chapters’ present various ideas that will benefit researchers, graduate students and engineers in this domain.
Future Research Directions in Computational Intelligence
Selected Papers from the 3rd EAI International Conference on Computational Intelligence and Communication
Häftad, Engelska, 2024
2 453 kr
Skickas inom 10-15 vardagar
This book presents select papers from 3rd EAI International Conference on Computational Intelligence and Communications (CICom 2022).
1 322 kr
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This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
1 283 kr
Skickas inom 10-15 vardagar
This book reviews the literature on hand posture estimation using generative methods, identifying the current gaps, such as sensitivity to hand shapes, sensitivity to a good initial posture, difficult hand posture recovery in cases of loss in tracking, and lack of addressing multiple objectives to maximize accuracy and minimize computational cost. To fill these gaps, it proposes a new 3D hand model that combines the best features of the current 3D hand models in the literature. It also discusses the development of a hand shape optimization technique. To find the global optimum for the single-objective problem formulated, it improves and applies particle swarm optimization (PSO), one of the most highly regarded optimization algorithms and one that is used successfully in both science and industry. After formulating the problem, multi-objective particle swarm optimization (MOPSO) is employed to estimate the Pareto optimal front as the solution for this bi-objective problem. The book alsodemonstrates the effectiveness of the improved PSO in hand posture recovery in cases of tracking loss. Lastly, the book examines the formulation of hand posture estimation as a bi-objective problem for the first time.The case studies included feature 50 hand postures extracted from five standard datasets, and were used to benchmark the proposed 3D hand model, hand shape optimization, and hand posture recovery.
911 kr
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This book reviews the literature on hand posture estimation using generative methods, identifying the current gaps, such as sensitivity to hand shapes, sensitivity to a good initial posture, difficult hand posture recovery in cases of loss in tracking, and lack of addressing multiple objectives to maximize accuracy and minimize computational cost.
Del 435 - Lecture Notes in Networks and Systems
Proceedings of International Conference on Communication and Artificial Intelligence
ICCAI 2021
Häftad, Engelska, 2022
2 666 kr
Skickas inom 10-15 vardagar
This book is a collection of best selected research papers presented at the International Conference on Communication and Artificial Intelligence (ICCAI 2021), held in the Department of Electronics & Communication Engineering, GLA University, Mathura, India, during 19–20 November 2021.
Del 959 - Lecture Notes in Electrical Engineering
Intelligent Systems and Applications
Select Proceedings of ICISA 2022
Inbunden, Engelska, 2022
3 198 kr
Skickas inom 10-15 vardagar
The contents of this volume focus on novel and modified artificial intelligence and machine learning-based methods and their applications in robotics, pharmaceutics, banking & finance, agriculture, food processing, crime prevention, smart homes, transportation, traffic control, and wildlife conservation, etc.
1 921 kr
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This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
1 921 kr
Skickas inom 10-15 vardagar
This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
1 921 kr
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It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization.
1 921 kr
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It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization.
1 602 kr
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It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental learning, and grey wolf optimizer for training neural networks.