Advances in Evolutionary Algorithms, Chang Wook Ahn
Автор: Jansen Название: Analyzing Evolutionary Algorithms ISBN: 3642173381 ISBN-13(EAN): 9783642173387 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Невозможна поставка. Описание: By adopting a complexity-theoretical perspective, he derives general limitations for black-box optimization, yielding lower bounds on the performance of evolutionary algorithms, and then develops general methods for deriving upper and lower bounds step by step.
Автор: Ashish Ghosh; Satchidananda Dehuri; Susmita Ghosh Название: Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases ISBN: 3642096158 ISBN-13(EAN): 9783642096150 Издательство: Springer Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Genetic Algorithm for Optimization of Multiple Objectives in Knowledge Discovery from Large Databases.- Knowledge Incorporation in Multi-objective Evolutionary Algorithms.- Evolutionary Multi-objective Rule Selection for Classification Rule Mining.- Rule Extraction from Compact Pareto-optimal Neural Networks.- On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection.- Classification and Survival Analysis Using Multi-objective Evolutionary Algorithms.- Clustering Based on Genetic Algorithms.
Автор: Crina Grosan; Ajith Abraham; Hisao Ishibuchi Название: Hybrid Evolutionary Algorithms ISBN: 3642092357 ISBN-13(EAN): 9783642092350 Издательство: Springer Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms." This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
Автор: Ventura Название: Pattern Mining with Evolutionary Algorithms ISBN: 3319338579 ISBN-13(EAN): 9783319338576 Издательство: Springer Рейтинг: Цена: 88500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions.
This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns.
A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.
Автор: Xinjie Yu; Mitsuo Gen Название: Introduction to Evolutionary Algorithms ISBN: 144712569X ISBN-13(EAN): 9781447125693 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduction to Evolutionary Algorithms presents a comprehensive, up-to-date overview of evolutionary algorithms. Readers will find a discussion of hot topics in the field, including genetic algorithms, differential evolution, swarm intelligence, and artificial immune systems.
Автор: Kay Chen Tan; Eik Fun Khor; Tong Heng Lee Название: Multiobjective Evolutionary Algorithms and Applications ISBN: 1849969353 ISBN-13(EAN): 9781849969352 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. Covers the authors` recent research in the area of multiobjective evolutionary algorithms as well as its practical applications.
Автор: F.J. Lobo; Cl?udio F. Lima; Zbigniew Michalewicz Название: Parameter Setting in Evolutionary Algorithms ISBN: 3540694315 ISBN-13(EAN): 9783540694311 Издательство: Springer Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Covers a broad area of evolutionary computation, including genetic algorithms, genetic programming, and estimation of distribution algorithms. This book discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications.
Автор: Ying-ping Chen Название: Exploitation of Linkage Learning in Evolutionary Algorithms ISBN: 3642263275 ISBN-13(EAN): 9783642263279 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The exploitation of linkage learning is enhancing the performance of evolutionary algorithms. This monograph examines recent progress in linkage learning, with a series of focused technical chapters that cover developments and trends in the field.
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