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عنوان
Soft Computing for Knowledge Discovery

پدید آورنده
by James G. Shanahan.

موضوع
Artificial intelligence.,Computer science.,Data structures (Computer science).,Logic, Symbolic and mathematical.

رده

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
9781461369479
(Number (ISBN
9781461543350

NATIONAL BIBLIOGRAPHY NUMBER

Number
b403277

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Soft Computing for Knowledge Discovery
General Material Designation
[Book]
Other Title Information
Introducing Cartesian Granule Features /
First Statement of Responsibility
by James G. Shanahan.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Boston, MA :
Name of Publisher, Distributor, etc.
Imprint: Springer,
Date of Publication, Distribution, etc.
2000.

SERIES

Series Title
Springer International Series in Engineering and Computer Science,
Volume Designation
570
ISSN of Series
0893-3405 ;

SUMMARY OR ABSTRACT

Text of Note
Knowledge discovery is an area of computer science that attempts to uncover interesting and useful patterns in data that permit a computer to perform a task autonomously or assist a human in performing a task more efficiently. Soft Computing for Knowledge Discovery provides a self-contained and systematic exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspective. It focuses on knowledge representation, machine learning, and the key methodologies that make up the fabric of soft computing - fuzzy set theory, fuzzy logic, evolutionary computing, and various theories of probability (e.g. naïve Bayes and Bayesian networks, Dempster-Shafer theory, mass assignment theory, and others). In addition to describing many state-of-the-art soft computing approaches to knowledge discovery, the author introduces Cartesian granule features and their corresponding learning algorithms as an intuitive approach to knowledge discovery. This new approach embraces the synergistic spirit of soft computing and exploits uncertainty in order to achieve tractability, transparency and generalization. Parallels are drawn between this approach and other well known approaches (such as naive Bayes and decision trees) leading to equivalences under certain conditions. The approaches presented are further illustrated in a battery of both artificial and real-world problems. Knowledge discovery in real-world problems, such as object recognition in outdoor scenes, medical diagnosis and control, is described in detail. These case studies provide further examples of how to apply the presented concepts and algorithms to practical problems. The author provides web page access to an online bibliography, datasets, source codes for several algorithms described in the book, and other information. Soft Computing for Knowledge Discovery is for advanced undergraduates, professionals and researchers in computer science, engineering and business information systems who work or have an interest in the dynamic fields of knowledge discovery and soft computing.

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781461369479

PIECE

Title
Springer eBooks

TOPICAL NAME USED AS SUBJECT

Artificial intelligence.
Computer science.
Data structures (Computer science).
Logic, Symbolic and mathematical.

PERSONAL NAME - PRIMARY RESPONSIBILITY

Shanahan, James G.

CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY

SpringerLink (Online service)

ORIGINATING SOURCE

Date of Transaction
20190307162100.0

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

Y

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