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Biologically-Inspired Techniques For Knowledge Discovery And Data Mining, Alam



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Автор: Alam
Название:  Biologically-Inspired Techniques For Knowledge Discovery And Data Mining
ISBN: 9781466660786
Издательство: Eurospan
Классификация:
ISBN-10: 1466660783
Обложка/Формат: Hardback
Страницы: 375
Вес: 1.202 кг.
Дата издания: 30.06.2014
Серия: Advances in data mining and database management
Язык: English
Иллюстрации: Illustrations, black and white
Размер: 279 x 216 x 22
Читательская аудитория: Professional and scholarly
Ключевые слова: Educational equipment & technology, computer-aided learning (CAL)
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Поставляется из: Англии
Описание: Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques.Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.


Data Mining: Concepts and Techniques,

Автор: Jiawei Han
Название: Data Mining: Concepts and Techniques,
ISBN: 0123814790 ISBN-13(EAN): 9780123814791
Издательство: Elsevier Science
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Цена: 10645 р.
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Описание: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

Biologically Inspired Approaches for Locomotion, Anomaly Detection and Reconfiguration for Walking Robots

Автор: Jakimovski
Название: Biologically Inspired Approaches for Locomotion, Anomaly Detection and Reconfiguration for Walking Robots
ISBN: 3642225047 ISBN-13(EAN): 9783642225048
Издательство: Springer
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Цена: 21428 р.
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Описание: The increasing presence of mobile robots in our everyday lives introduces the requirements for their intelligent and autonomous features. Therefore the next generation of mobile robots should be more self-capable, in respect to: increasing of their functionality in unforeseen situations, decreasing of the human involvement in their everyday operations and their maintenance; being robust; fault tolerant and reliable in their operation.Although mobile robotic systems have been a topic of research for decades and aside the technology improvements nowadays, the subject on how to program and making them more autonomous in their operations is still an open field for research.Applying bio-inspired, organic approaches in robotics domain is one of the methodologies that are considered that would help on making the robots more autonomous and self-capable, i.e. having properties such as: self-reconfiguration, self-adaptation, self-optimization, etc.In this book several novel biologically inspired approaches for walking robots (multi-legged and humanoid) domain are introduced and elaborated. They are related to self-organized and self-stabilized robot walking, anomaly detection within robot systems using self-adaptation, and mitigating the faulty robot conditions by self-reconfiguration of a multi-legged walking robot. The approaches presented have been practically evaluated in various test scenarios, the results from the experiments are discussed in details and their practical usefulness is validated.

Biologically Inspired Signal Processing for Chemical Sensing

Автор: Agust?n Guti?rrez; Santiago Marco
Название: Biologically Inspired Signal Processing for Chemical Sensing
ISBN: 3642101216 ISBN-13(EAN): 9783642101212
Издательство: Springer
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Цена: 18594 р.
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Описание: This volume presents a collection of research advances in biologically inspired signal processing for chemical sensing. The book provides background on the olfactory system and some bio-inspired approaches to processing chemical sensor signals.

Biologically-Inspired Optimisation Methods

Автор: Andrew Lewis; Sanaz Mostaghim; Marcus Randall
Название: Biologically-Inspired Optimisation Methods
ISBN: 3642012612 ISBN-13(EAN): 9783642012617
Издательство: Springer
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Цена: 28609 р.
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Описание: This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

Biologically-Inspired Optimisation Methods

Автор: Andrew Lewis; Sanaz Mostaghim; Marcus Randall
Название: Biologically-Inspired Optimisation Methods
ISBN: 3642101771 ISBN-13(EAN): 9783642101779
Издательство: Springer
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Цена: 28608 р.
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Описание: This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

Improving Knowledge Discovery Through The Integration Of Data Mining Techniques

Автор: Usman
Название: Improving Knowledge Discovery Through The Integration Of Data Mining Techniques
ISBN: 1466685131 ISBN-13(EAN): 9781466685130
Издательство: Eurospan
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Цена: 38975 р.
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Описание: Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other’s methods to facilitate knowledge discovery.Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 9523 р.
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Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Data Mining and Knowledge Discovery for Geoscientists

Автор: Guangren Shi
Название: Data Mining and Knowledge Discovery for Geoscientists
ISBN: 0124104371 ISBN-13(EAN): 9780124104372
Издательство: Elsevier Science
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Цена: 16422 р.
Наличие на складе: Нет в наличии.

Описание: Addresses challenges by summarizing the developments in geosciences data mining and arming scientists with the ability to apply key concepts to effectively analyze and interpret vast amounts of critical information. This title focuses on 22 of data mining`s practical algorithms and application samples.


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