Multi Objective Evolutionary Algorithms For Knowledge Discovery From Databases
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Multi Objective Evolutionary Algorithms For Knowledge Discovery From Databases
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Author : Ashish Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-19
Multi Objective Evolutionary Algorithms For Knowledge Discovery From Databases written by Ashish Ghosh 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 2008-03-19 with Mathematics categories.
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.
Multi Objective Optimization Using Evolutionary Algorithms
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Author : Kalyanmoy Deb
language : en
Publisher: John Wiley & Sons
Release Date : 2001-07-05
Multi Objective Optimization Using Evolutionary Algorithms written by Kalyanmoy Deb 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 2001-07-05 with Mathematics categories.
Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme der Ingenieurtechnik, der Vorhersage und der Planung anzuwenden. Der Autor gibt auch einen Ausblick auf Forschungsaufgaben der Zukunft.
Metaheuristics For Big Data
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Author : Clarisse Dhaenens
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-29
Metaheuristics For Big Data written by Clarisse Dhaenens 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 2016-08-29 with Computers categories.
Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.
Knowledge Mining Using Intelligent Agents
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Author : Satchidananda Dehuri
language : en
Publisher: World Scientific
Release Date : 2011
Knowledge Mining Using Intelligent Agents written by Satchidananda Dehuri and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.
Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability through the use of intelligent agents like ants, termites and honey bees. In order to provide readers with an integrated set of concepts and techniques for understanding knowledge discovery and its practical utility, this book blends two distinct disciplines data mining and knowledge discovery process, and intelligent agents-based computing (swarm intelligence and computational intelligence). For the more advanced reader, researchers, and decision/policy-makers are given an insight into emerging technologies and their possible hybridization, which can be used for activities like dredging, capturing, distributions and the utilization of knowledge in their domain of interest (i.e. business, policy-making, etc.). By studying the behavior of swarm intelligence, this book aims to integrate the computational intelligence paradigm and intelligent distributed agents architecture to optimize various engineering problems and efficiently represent knowledge from the large gamut of data.
Data Mining And Knowledge Discovery With Evolutionary Algorithms
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Author : Alex A. Freitas
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Data Mining And Knowledge Discovery With Evolutionary Algorithms written by Alex A. Freitas 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 2013-11-11 with Computers categories.
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
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.
Evolutionary Computation In Data Mining
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Author : Ashish Ghosh
language : en
Publisher: Springer
Release Date : 2009-09-02
Evolutionary Computation In Data Mining written by Ashish Ghosh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-02 with Computers categories.
Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive. The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation).
Evolutionary Algorithms For Solving Multi Objective Problems
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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-18
Evolutionary Algorithms For Solving Multi Objective Problems 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 2007-09-18 with Computers categories.
This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.
Applications Of Multi Objective Evolutionary Algorithms
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Author : Carlos A Coello Coello
language : en
Publisher: World Scientific
Release Date : 2004-12-08
Applications Of Multi Objective Evolutionary Algorithms written by Carlos A Coello Coello and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-08 with Computers categories.
This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.
Data Mining And Knowledge Discovery With Evolutionary Algorithms
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Author : Freitas Alex A.
language : en
Publisher:
Release Date : 2007-10-01
Data Mining And Knowledge Discovery With Evolutionary Algorithms written by Freitas Alex A. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-01 with categories.