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Applied intelligent decision making in machine learning, 


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Название:  Applied intelligent decision making in machine learning
ISBN: 9780367503369
Издательство: Taylor&Francis
Классификация:

ISBN-10: 0367503360
Обложка/Формат: Hardcover
Страницы: 252
Вес: 0.54 кг.
Дата издания: 19.11.2020
Серия: Computational intelligence in engineering problem solving
Язык: English
Иллюстрации: 68 tables, black and white; 113 illustrations, black and white
Размер: 162 x 241 x 23
Читательская аудитория: Tertiary education (us: college)
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Поставляется из: Европейский союз
Описание: The objective of this edited book is to share outcomes on various research domains to develop efficient, adaptive and intelligent models to handle the challenges related to decision making in various aspects. It incorporates the advances of machine intelligent techniques in decision making process and its applications.


Ascent of gim, the global intelligent machine

Автор: Koetsier, Teun
Название: Ascent of gim, the global intelligent machine
ISBN: 3319965468 ISBN-13(EAN): 9783319965468
Издательство: Springer
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Цена: 13974.00 р.
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Описание: In the concluding chapters of this book the author introduces GIM, the Global Intelligent Machine.

Human Centered Intelligent Infrastructure

Автор: Dahashi
Название: Human Centered Intelligent Infrastructure
ISBN: 147247144X ISBN-13(EAN): 9781472471444
Издательство: Taylor&Francis
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Цена: 12248.00 р.
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Описание: This book considers the challenges placed on users of current and future condition monitoring systems. Its primary focus is understanding the cognitive processes, including managing alarms, interpreting data, and collaborating with automation.

A Paraconsistent Decision-Making Method

Автор: Carvalho
Название: A Paraconsistent Decision-Making Method
ISBN: 3319741098 ISBN-13(EAN): 9783319741093
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Decision analysis is useful in making choices when the consequences of actions are uncertain, like in business administration, where it assists in making investment decisions, and in health care, Decision analysis is also valuable when the possible actions may lead to conflicting consequences.

Applied Intelligent Systems

Автор: John Fulcher
Название: Applied Intelligent Systems
ISBN: 3642059422 ISBN-13(EAN): 9783642059421
Издательство: Springer
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Цена: 26120.00 р.
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Описание: Humans have always been hopeless at predicting the future...most people now generally agree that the margin of viability in prophecy appears to be 1 ten years. Even sophisticated research endeavours in this arena tend to go 2 off the rails after a decade or so. The computer industry has been particularly prone to bold (and often way off the mark) predictions, for example: 'I think there is a world market for maybe five computers' Thomas J. Watson, IBM Chairman (1943), 'I have traveled the length and breadth of this country and talked with the best people, and I can assure you that data processing is a fad that won't last out the year' Prentice Hall Editor (1957), 'There is no reason why anyone would want a computer in their home' Ken Olsen, founder of DEC (1977) and '640K ought to be enough for anybody' Bill Gates, CEO Microsoft (1981). 3 The field of Artificial Intelligence - right from its inception - has been particularly plagued by 'bold prediction syndrome', and often by leading practitioners who should know better. AI has received a lot of bad press 4 over the decades, and a lot of it deservedly so. How often have we groaned in despair at the latest 'by the year-20xx, we will all have...(insert your own particular 'hobby horse' here - e. g.

Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

Автор: Hinders Mark K.
Название: Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint
ISBN: 3030493946 ISBN-13(EAN): 9783030493943
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals.

Planning and Decision Making for Aerial Robots

Автор: Yasmina Bestaoui Sebbane
Название: Planning and Decision Making for Aerial Robots
ISBN: 3319037064 ISBN-13(EAN): 9783319037066
Издательство: Springer
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Цена: 20896.00 р.
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Описание: This book provides an introduction to planning and decision making for aerial robots, including motion planning, deterministic decision making, decision making under uncertainty, and multi-robot planning. It includes case studies.

Planning and Decision Making for Aerial Robots

Автор: Yasmina Bestaoui Sebbane
Название: Planning and Decision Making for Aerial Robots
ISBN: 3319344757 ISBN-13(EAN): 9783319344751
Издательство: Springer
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Цена: 18284.00 р.
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Описание: This book provides an introduction to planning and decision making for aerial robots, including motion planning, deterministic decision making, decision making under uncertainty, and multi-robot planning. It includes case studies.

Fuzzy and Multi-Level Decision Making

Автор: E. Stanley Lee; Hsu-shih Shih
Название: Fuzzy and Multi-Level Decision Making
ISBN: 144711177X ISBN-13(EAN): 9781447111771
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Managerial Decisions in hierarchy organizations, such as the various manufacturing and service companies, are difficult to formalize and even more difficult to optimize. The concepts of fuzzy set and fuzzy linguistic representation, which form an integral part of any managerial decision, are also discussed.

Analysis and Decision Making in Uncertain Systems

Автор: Zdzislaw Bubnicki
Название: Analysis and Decision Making in Uncertain Systems
ISBN: 1849969094 ISBN-13(EAN): 9781849969093
Издательство: Springer
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Цена: 20896.00 р.
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Описание: A unified and systematic description of analysis and decision problems within a wide class of uncertain systems, described by traditional mathematical methods and by relational knowledge representations. Prof. Bubnicki takes a unique approach to stability and stabilization of uncertain systems.

Fuzzy Approach to Reasoning and Decision-Making

Автор: Vil?m Nov?k; Jaroslav Ram?k; Milan Mares; Martin C
Название: Fuzzy Approach to Reasoning and Decision-Making
ISBN: 9401052220 ISBN-13(EAN): 9789401052221
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Selected Papers of the International Symposium held at Bechyne, June 25-29, 1990

CyberPhysical Systems: Decision Making Mechanisms and Applications

Автор: Kostas Siozios, Dimitrios Soudris, Elias Kosmatopoulos
Название: CyberPhysical Systems: Decision Making Mechanisms and Applications
ISBN: 8793609094 ISBN-13(EAN): 9788793609099
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание: Describes essential theory, recent research and large-scale usecases that addresses urgent challenges in Cyber-Physical System (CPS) architectures, including chapters on decision making for large scale CPS; modeling of CPS with emphasis at the control mechanisms; hardware/software implementation of the control mechanisms; and fault-tolerant and reliability issues for the control mechanisms,

Applied genetic programming and machine learning

Автор: Iba, Hitoshi Hasegawa, Yoshihiko Paul, Topon Kumar
Название: Applied genetic programming and machine learning
ISBN: 0367385279 ISBN-13(EAN): 9780367385279
Издательство: Taylor&Francis
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Цена: 9492.00 р.
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Описание:

What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications.

Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the search process through the design of objective fitness functions, and examine the search performance of the evolutionary system. It provides a methodology for integrating GP and machine learning techniques, establishing a robust evolutionary framework for addressing tasks from areas such as chaotic time-series prediction, system identification, financial forecasting, classification, and data mining.

The book provides a starting point for the research of extended GP frameworks with the integration of several machine learning schemes. Drawing on empirical studies taken from fields such as system identification, finanical engineering, and bio-informatics, it demonstrates how the proposed methodology can be useful in practical inductive problem solving.


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