Multiobjective Genetic Algorithms for Clustering

Multiobjective Genetic Algorithms for Clustering PDF Author: Ujjwal Maulik
Publisher: Springer Science & Business Media
ISBN: 3642166156
Category : Computers
Languages : en
Pages : 292

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Book Description
This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

Multiobjective Genetic Algorithms for Clustering

Multiobjective Genetic Algorithms for Clustering PDF Author: Ujjwal Maulik
Publisher: Springer Science & Business Media
ISBN: 3642166156
Category : Computers
Languages : en
Pages : 292

Get Book Here

Book Description
This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

Multiobjective Genetic Algorithms for Clustering

Multiobjective Genetic Algorithms for Clustering PDF Author:
Publisher: Springer
ISBN: 9783642166167
Category :
Languages : en
Pages : 300

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Book Description


Evolutionary Data Clustering: Algorithms and Applications

Evolutionary Data Clustering: Algorithms and Applications PDF Author: Ibrahim Aljarah
Publisher: Springer Nature
ISBN: 9813341912
Category : Technology & Engineering
Languages : en
Pages : 248

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Book Description
This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. 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. The book also covers applications of evolutionary data clustering in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases PDF Author: Ashish Ghosh
Publisher: Springer Science & Business Media
ISBN: 3540774661
Category : Mathematics
Languages : en
Pages : 169

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Book Description
The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.

Applications of Multi-objective Evolutionary Algorithms

Applications of Multi-objective Evolutionary Algorithms PDF Author: Carlos A. Coello Coello
Publisher: World Scientific
ISBN: 9812561064
Category : Computers
Languages : en
Pages : 792

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Book Description
- Detailed MOEA applications discussed by international experts - State-of-the-art practical insights in tackling statistical optimization with MOEAs - A unique monograph covering a wide spectrum of real-world applications - Step-by-step discussion of MOEA applications in a variety of domains

Circuit Clustering for Cluster-based FPGAs Using Novel Multiobjective Genetic Algorithms

Circuit Clustering for Cluster-based FPGAs Using Novel Multiobjective Genetic Algorithms PDF Author: Yuan Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Artificial Neural Nets and Genetic Algorithms

Artificial Neural Nets and Genetic Algorithms PDF Author: Rudolf F. Albrecht
Publisher: Springer Science & Business Media
ISBN: 370917533X
Category : Computers
Languages : en
Pages : 752

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Book Description
Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume. There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected. Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.

Genetic Algorithms and Grouping Problems

Genetic Algorithms and Grouping Problems PDF Author: Emanuel Falkenauer
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 248

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Book Description
A reader-friendly introduction to the exciting, vast potential of Genetic Algorithms. The book gives readers a general understanding of the concepts underlying the technology, an insight into its perceived benefits and failings, and a clear and practical illustration of how optimization problems can be solved more efficiently using Falkenauer's new class of algorithms.

Parallel Problem Solving from Nature - PPSN VIII

Parallel Problem Solving from Nature - PPSN VIII PDF Author: Xin Yao
Publisher: Springer Science & Business Media
ISBN: 3540230920
Category : Computers
Languages : en
Pages : 1204

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Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Parallel Problem Solving from Nature, PPSN 2004, held in Birmingham, UK, in September 2004. The 119 revised full papers presented were carefully reviewed and selected from 358 submissions. The papers address all current issues in biologically inspired computing; they are organized in topical sections on theoretical and foundational issues, new algorithms, applications, multi-objective optimization, co-evolution, robotics and multi-agent systems, and learning classifier systems and data mining.

Evolutionary Multi-Criterion Optimization

Evolutionary Multi-Criterion Optimization PDF Author: Carlos Coello Coello
Publisher: Springer
ISBN: 9783540318804
Category : Computers
Languages : en
Pages : 0

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Book Description