Автор: Ray Jhuma, Mukherjee Anirban, Dey Sadhan Kumar Название: Metaheuristic Approaches to Portfolio Optimization ISBN: 1522592946 ISBN-13(EAN): 9781522592945 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 19437.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Examines the proper selection of financial instruments in a financial portfolio management scenario in terms of metaheuristic approaches. The book explores measures used for the evaluation of risks/returns of portfolios in real-life situations, and features research on topics such as closed-end funds, asset allocation, and the risk-return paradigm.
Автор: Cuevas Erik, Diaz Primitivo, Camarena Octavio Название: Metaheuristic Computation: A Performance Perspective ISBN: 3030580997 ISBN-13(EAN): 9783030580995 Издательство: Springer Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments.
Автор: Cuevas, Erik , Rodriguez, Alma Название: Metaheuristic Computation with MATLAB® ISBN: 0367438860 ISBN-13(EAN): 9780367438869 Издательство: Taylor&Francis Рейтинг: Цена: 18374.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The main purpose of this book is to provide a unified view of the most popular metaheuristic methods. Under this perspective, it has presented the fundamental design principles as well as the operators of metaheuristic approaches which are considered essential.
Автор: Hadj Ahmed Bouarara , Reda Mohamed Hamou , Amine Rahmani (Editors) Название: Advanced metaheuristic methods in big data retrieval and analytics / ISBN: 1522573380 ISBN-13(EAN): 9781522573388 Издательство: Turpin Рейтинг: Цена: 34373.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The amount of data shared and stored on the web and other document repositories is steadily on the rise. Unfortunately, this growth increases inefficiencies and difficulties when trying to find the most relevant and up-to-date information due to unstructured data.Advanced Metaheuristic Methods in Big Data Retrieval and Analytics examines metaheuristic techniques as an important alternative model for solving complex problems that are not treatable by deterministic methods. Recent studies suggest that IR and biomimicry can be used together for several application problems in big data and internet of things, especially when conventional methods would be too expensive or difficult to implement. Featuring coverage on a broad range of topics such as ontology, plagiarism detection, and machine learning, this book is ideally designed for engineers, graduate students, IT professionals, and academicians seeking an overview of new trends in information retrieval in big data.
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).
Автор: Cuevas Erik, Rodrнguez Alma, Alejo-Reyes Avelina Название: Recent Metaheuristic Computation Schemes in Engineering ISBN: 3030660060 ISBN-13(EAN): 9783030660062 Издательство: Springer Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem.
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;
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
Описание: Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends is a collection of the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing. Providing researchers, practitioners, and academicians with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization, this book compile the latest findings, analysis, improvements, and applications of technologies within metaheuristic computing.
Автор: Enrique Alba; Rafael Mart? Название: Metaheuristic Procedures for Training Neural Networks ISBN: 1441941282 ISBN-13(EAN): 9781441941282 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides successful implementations of metaheuristic methods for neural network training. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own.
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