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Artificial intelligent methods for h...

Verstraete, Jorg.

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Artificial intelligent methods for handling spatial data = fuzzy rulebase systems and gridded data problems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligent methods for handling spatial data/ by Jorg Verstraete.
Reminder of title:	fuzzy rulebase systems and gridded data problems /
Author:	Verstraete, Jorg.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xvi, 135 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Problem Description and Related Work -- Concept -- Fuzzy Rulebase Systems -- Parameters and most Possible Ranges -- Rulebase Construction -- Constrained Defuzziﬁcation -- Data Comparison -- Experiments -- Conclusion.
Contained By:	Springer eBooks
Subject:	Data mining - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-030-00238-1
ISBN:	9783030002381

Artificial intelligent methods for handling spatial data = fuzzy rulebase systems and gridded data problems /
Verstraete, Jorg.

Artificial intelligent methods for handling spatial datafuzzy rulebase systems and gridded data problems /[electronic resource] :by Jorg Verstraete. - Cham :Springer International Publishing :2019. - xvi, 135 p. :ill. (some col.), digital ;24 cm. - Studies in fuzziness and soft computing,v.3701434-9922 ;. - Studies in fuzziness and soft computing ;v.370..

Introduction -- Problem Description and Related Work -- Concept -- Fuzzy Rulebase Systems -- Parameters and most Possible Ranges -- Rulebase Construction -- Constrained Defuzziﬁcation -- Data Comparison -- Experiments -- Conclusion.

This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases. It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.

ISBN: 9783030002381

Standard No.: 10.1007/978-3-030-00238-1doiSubjects--Topical Terms:

898856
Data mining
--Data processing.

LC Class. No.: QA76.9.D343 / V47 2019

Dewey Class. No.: 006.312

Artificial intelligent methods for handling spatial data = fuzzy rulebase systems and gridded data problems /
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245 1 0 $a Artificial intelligent methods for handling spatial data $h [electronic resource] : $b fuzzy rulebase systems and gridded data problems / $c by Jorg Verstraete.
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300 $a xvi, 135 p. : $b ill. (some col.), digital ; $c 24 cm.
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505 0 $a Introduction -- Problem Description and Related Work -- Concept -- Fuzzy Rulebase Systems -- Parameters and most Possible Ranges -- Rulebase Construction -- Constrained Defuzziﬁcation -- Data Comparison -- Experiments -- Conclusion.
520 $a This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases. It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.
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