Multidimensional Particle Swarm Optimization For Machine Learning And Pattern Recognition
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Multidimensional Particle Swarm Optimization For Machine Learning And Pattern Recognition
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Author : Serkan Kiranyaz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-07-16
Multidimensional Particle Swarm Optimization For Machine Learning And Pattern Recognition written by Serkan Kiranyaz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-16 with Computers categories.
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.
Swarm Intelligence For Multi Objective Problems In Data Mining
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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-09-28
Swarm Intelligence For Multi Objective Problems In Data Mining written by Carlos Coello Coello and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-28 with Mathematics categories.
The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.
Fractional Order Darwinian Particle Swarm Optimization
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Author : Micael Couceiro
language : en
Publisher: Springer
Release Date : 2015-06-16
Fractional Order Darwinian Particle Swarm Optimization written by Micael Couceiro and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-16 with Technology & Engineering categories.
This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, such as its ability to provide an improved convergence towards a solution, while avoiding sub-optimality. This book offers a valuable resource for researchers in the fields of robotics, sports science, pattern recognition and machine learning, as well as for students of electrical engineering and computer science.
Swarm Intelligence And Bio Inspired Computation
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Author : Shichang Sun
language : en
Publisher: Elsevier Inc. Chapters
Release Date : 2013-05-16
Swarm Intelligence And Bio Inspired Computation written by Shichang Sun and has been published by Elsevier Inc. Chapters this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-16 with Computers categories.
In this chapter, we present the convergence analysis and applications of particle swarm optimization algorithm. Although it is difficult to analyze the convergence of this algorithm, we discuss its convergence based on its iterated function system and probabilistic theory. The dynamic trajectory of the particle is described based on single individual. We also attempt to theoretically prove that the swarm algorithm converges with a probability of 1 toward the global optimal. We apply the algorithms to solve the scheduling problem and peer-to-peer neighbor selection problem. This chapter is also concerned to employ the nature-inspired optimization methods in machine learning. We introduce the swarm algorithm to reoptimize hidden Markov models.
Advances In Swarm Intelligence Part I
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2011-05-31
Advances In Swarm Intelligence Part I written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-31 with Computers categories.
The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.
Advances In Intelligent Informatics
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Author : El-Sayed M. El-Alfy
language : en
Publisher: Springer
Release Date : 2014-09-08
Advances In Intelligent Informatics written by El-Sayed M. El-Alfy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-08 with Technology & Engineering categories.
This book contains a selection of refereed and revised papers of Intelligent Informatics Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India. The papers selected for this Track cover several intelligent informatics and related topics including signal processing, pattern recognition, image processing data mining and their applications.
Swarm Intelligence And Bio Inspired Computation
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Author : Simon Fong
language : en
Publisher: Elsevier Inc. Chapters
Release Date : 2013-05-16
Swarm Intelligence And Bio Inspired Computation written by Simon Fong and has been published by Elsevier Inc. Chapters this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-16 with Computers categories.
Data mining has evolved from methods of simple statistical analysis to complex pattern recognition in the past decades. During the progression, the data mining algorithms are modified or extended in order to overcome some specific problems. This chapter discusses about the prospects of improving data mining algorithms by integrating bio-inspired optimization, which has lately captivated much of researchers’ attention. In particular, high dimensionality and the unavailability of the whole data set (as in stream mining) in the training data have known to be two major challenges. We demonstrated that these two challenges, through two small examples such as K-means clustering and time-series classification, can be overcome by integrating data mining and bio-inspired algorithms.
Particle Swarm Optimization
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Author : Maurice Clerc
language : en
Publisher: John Wiley & Sons
Release Date : 2013-03-04
Particle Swarm Optimization written by Maurice Clerc and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-04 with Computers categories.
This is the first book devoted entirely to Particle SwarmOptimization (PSO), which is a non-specific algorithm, similar toevolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly beenapplied to continuous-discrete heterogeneous strongly non-linearnumerical optimization and it is thus used almost everywhere in theworld. Its convergence rate also makes it a preferred tool indynamic optimization.
Design Of A Superconducting Dc Wind Generator
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Author : Liu, Yingzhen
language : en
Publisher: KIT Scientific Publishing
Release Date : 2020-11-18
Design Of A Superconducting Dc Wind Generator written by Liu, Yingzhen and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-18 with Technology & Engineering categories.
The trend towards larger power ratings of wind turbines asks for innovations in power generation, which requires lower weight and cost, smaller size, higher efficiency and reliability. Due to high current-carrying capability and no DC losses of superconductors, a superconducting wind generator can have a superior power to weight/volume ratio with high efficiency. The work in the book mainly focuses on the feasibility study and design of a superconducting DC wind generator.
Fundamentals Of Computational Intelligence
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Author : James M. Keller
language : en
Publisher: John Wiley & Sons
Release Date : 2016-07-12
Fundamentals Of Computational Intelligence written by James M. Keller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-12 with Technology & Engineering categories.
Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.