Particle Swarm Optimization PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Particle Swarm Optimization PDF full book. Access full book title Particle Swarm Optimization by Maurice Clerc. Download full books in PDF and EPUB format.
Author: Maurice Clerc
Publisher: John Wiley & Sons
ISBN: 0470394439
Category : Computers
Languages : en
Pages : 245
Get Book Here
Book Description
This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly been applied to continuous-discrete heterogeneous strongly non-linear numerical optimization and it is thus used almost everywhere in the world. Its convergence rate also makes it a preferred tool in dynamic optimization.
Author: Maurice Clerc
Publisher: John Wiley & Sons
ISBN: 0470394439
Category : Computers
Languages : en
Pages : 245
Get Book Here
Book Description
This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly been applied to continuous-discrete heterogeneous strongly non-linear numerical optimization and it is thus used almost everywhere in the world. Its convergence rate also makes it a preferred tool in dynamic optimization.
Author: Maurice Clerc
Publisher: Wiley-ISTE
ISBN:
Category : Computers
Languages : en
Pages : 254
Get Book Here
Book Description
Focuses on PSO, a non-specific algorithm inspired by the social behaviour of flocks of birds or shoals of fish. A PSO system combines local and global search methods, attempting to balance exploration with exploitation. This book includes various such source programs.
Author: Burcu Adıgüzel Mercangöz
Publisher: Springer Nature
ISBN: 3030702812
Category : Business & Economics
Languages : en
Pages : 355
Get Book Here
Book Description
This book explains the theoretical structure of particle swarm optimization (PSO) and focuses on the application of PSO to portfolio optimization problems. The general goal of portfolio optimization is to find a solution that provides the highest expected return at each level of portfolio risk. According to H. Markowitz’s portfolio selection theory, as new assets are added to an investment portfolio, the total risk of the portfolio’s decreases depending on the correlations of asset returns, while the expected return on the portfolio represents the weighted average of the expected returns for each asset. The book explains PSO in detail and demonstrates how to implement Markowitz’s portfolio optimization approach using PSO. In addition, it expands on the Markowitz model and seeks to improve the solution-finding process with the aid of various algorithms. In short, the book provides researchers, teachers, engineers, managers and practitioners with many tools they need to apply the PSO technique to portfolio optimization.
Author: Jun Sun
Publisher: CRC Press
ISBN: 1439835772
Category : Computers
Languages : en
Pages : 419
Get Book Here
Book Description
Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives, the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle swarm optimisation (QPSO) algorithm. This globally convergent algorithm has fewer parameters, a faster convergence rate, and stronger searchability for complex problems. The book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles of the PSO algorithm. Examples illustrate how the PSO algorithm solves optimisation problems. The authors also analyse the reasons behind the shortcomings of the PSO algorithm. Moving on to the QPSO algorithm, the authors give a thorough overview of the literature on QPSO, describe the fundamental model for the QPSO algorithm, and explore applications of the algorithm to solve typical optimisation problems. They also discuss some advanced theoretical topics, including the behaviour of individual particles, global convergence, computational complexity, convergence rate, and parameter selection. The text closes with coverage of several real-world applications, including inverse problems, optimal design of digital filters, economic dispatch problems, biological multiple sequence alignment, and image processing. MATLAB®, Fortran, and C++ source codes for the main algorithms are provided on an accompanying downloadable resources. Helping you numerically solve optimisation problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. It not only explains how to use the algorithms, but also covers advanced topics that establish the groundwork for understanding.
Author: Parsopoulos, Konstantinos E.
Publisher: IGI Global
ISBN: 1615206671
Category : Business & Economics
Languages : en
Pages : 328
Get Book Here
Book Description
"This book presents the most recent and established developments of Particle swarm optimization (PSO) within a unified framework by noted researchers in the field"--Provided by publisher.
Author: Brian Walker
Publisher: Nova Science Publishers
ISBN: 9781536108286
Category : Electric power systems
Languages : en
Pages : 0
Get Book Here
Book Description
Particle swarm optimisation (PSO) is one of the recently developed swarm intelligent optimisation technologies that offer the advantages of simplicity and fast biological convergence. The technique originated from the theory of artificial life and evolution, which is based on the optimisation that is achieved as a result of swarm behaviour. PSO can be easily implemented due to fewer parameters for adjustment hence it has been applied broadly in various engineering fields. This book reviews advances in research and applications of PSO.
Author: Claude Sammut
Publisher: Springer Science & Business Media
ISBN: 0387307680
Category : Computers
Languages : en
Pages : 1061
Get Book Here
Book Description
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Author: Serkan Kiranyaz
Publisher: Springer Science & Business Media
ISBN: 3642378463
Category : Computers
Languages : en
Pages : 343
Get Book Here
Book Description
For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. The book will be of benefit to researchers and practitioners working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications.
Author: Andrea E. Olsson
Publisher:
ISBN: 9781616685270
Category : Mathematical optimization
Languages : en
Pages : 0
Get Book Here
Book Description
Particle swarm optimisation (PSO) is an algorithm modelled on swarm intelligence that finds a solution to an optimisation problem in a search space or model and predicts social behaviour in the presence of objectives. The PSO is a stochastic, population-based computer algorithm modelled on swarm intelligence. Swarm intelligence is based on social-psychological principles and provides insights into social behaviour, as well as contributing to engineering applications. This book presents information on particle swarm optimisation such as using mono-objective and multi-objective particle swarm optimisation for the tuning of process control laws; convergence issues in particle swarm optimisation; study on vehicle routing problems using enhanced particle swarm optimisation and others.
Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 412
Get Book Here
Book Description
Optimization happens everywhere. Machine learning is one example of such and gradient descent is probably the most famous algorithm for performing optimization. Optimization means to find the best value of some function or model. That can be the maximum or the minimum according to some metric. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will learn how to find the optimum point to numerical functions confidently using modern optimization algorithms.
