國立虎尾科技大學 |

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation = Proceedings of the INFUS 2021 Conference, held August 24-26, 2021. Volume 1 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation/ edited by Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari.
其他題名:	Proceedings of the INFUS 2021 Conference, held August 24-26, 2021. Volume 1 /
其他作者:	Sari, Irem Ucal.
面頁冊數:	XVIII, 954 p. 287 illus., 167 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-85626-7
ISBN:	9783030856267

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation = Proceedings of the INFUS 2021 Conference, held August 24-26, 2021. Volume 1 /
Intelligent and Fuzzy Techniques for Emerging Conditions and Digital TransformationProceedings of the INFUS 2021 Conference, held August 24-26, 2021. Volume 1 /[electronic resource] :edited by Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari. - 1st ed. 2022. - XVIII, 954 p. 287 illus., 167 illus. in color.online resource. - Lecture Notes in Networks and Systems,3072367-3389 ;. - Lecture Notes in Networks and Systems,1.

Fuzzy Clustering -- A Digital Twin-based Approach for the Fault Diagnosis of a Bearing -- Fuzzy Cluster analysis of Claustrophobia questionnaire data in Iranian male and female educated populations -- Data Driven Approach to Order Picking Time Prediction Using Fuzzy Clustering and ANN -- A Comparative Analysis of Fuzzy C-Means, K-Means, and K-Medoids Clustering Algorithms for Analysis Countries’ COVID-19 Risk -- Text Segmentation Using Light Syntax Parsing and Fuzzy Systems -- A Neighborhood Merging Policy Based on Shannon’s Entropy and Symmetric Relative Entropy for Non-Convex Cluster Detection.

This book presents recent research in intelligent and fuzzy techniques. Emerging conditions such as pandemic, wars, natural disasters and various high technologies force people for significant changes in business and social life. The adoption of digital technologies to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technologies through intelligent systems is the main scope of this book. It focuses on revealing the reflection of digital transformation in our business and social life under emerging conditions through intelligent and fuzzy systems. The latest intelligent and fuzzy methods and techniques on digital transformation are introduced by theory and applications. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc. and Ph.D. students studying digital transformation. Usage of ordinary fuzzy sets and their extensions, heuristics and metaheuristics from optimization to machine learning, from quality management to risk management makes the book an excellent source for researchers.

ISBN: 9783030856267

Standard No.: 10.1007/978-3-030-85626-7doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation = Proceedings of the INFUS 2021 Conference, held August 24-26, 2021. Volume 1 /
LDR:03353nam a22003975i 4500 001 1084398
003 DE-He213
005 20220119181601.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783030856267 $9 978-3-030-85626-7
024 7 $a 10.1007/978-3-030-85626-7 $2 doi
035 $a 978-3-030-85626-7
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation $h [electronic resource] : $b Proceedings of the INFUS 2021 Conference, held August 24-26, 2021. Volume 1 / $c edited by Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a XVIII, 954 p. 287 illus., 167 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Lecture Notes in Networks and Systems, $x 2367-3389 ; $v 307
505 0 $a Fuzzy Clustering -- A Digital Twin-based Approach for the Fault Diagnosis of a Bearing -- Fuzzy Cluster analysis of Claustrophobia questionnaire data in Iranian male and female educated populations -- Data Driven Approach to Order Picking Time Prediction Using Fuzzy Clustering and ANN -- A Comparative Analysis of Fuzzy C-Means, K-Means, and K-Medoids Clustering Algorithms for Analysis Countries’ COVID-19 Risk -- Text Segmentation Using Light Syntax Parsing and Fuzzy Systems -- A Neighborhood Merging Policy Based on Shannon’s Entropy and Symmetric Relative Entropy for Non-Convex Cluster Detection.
520 $a This book presents recent research in intelligent and fuzzy techniques. Emerging conditions such as pandemic, wars, natural disasters and various high technologies force people for significant changes in business and social life. The adoption of digital technologies to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technologies through intelligent systems is the main scope of this book. It focuses on revealing the reflection of digital transformation in our business and social life under emerging conditions through intelligent and fuzzy systems. The latest intelligent and fuzzy methods and techniques on digital transformation are introduced by theory and applications. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc. and Ph.D. students studying digital transformation. Usage of ordinary fuzzy sets and their extensions, heuristics and metaheuristics from optimization to machine learning, from quality management to risk management makes the book an excellent source for researchers.
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Data Engineering. $3 1226308
650 1 4 $a Computational Intelligence. $3 768837
650 0 $a Artificial intelligence. $3 559380
650 0 $a Engineering—Data processing. $3 1297966
650 0 $a Computational intelligence. $3 568984
700 1 $a Sari, Irem Ucal. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1247167
700 1 $a Tolga, A. Cagri. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1326268
700 1 $a Oztaysi, Basar. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1024327
700 1 $a Cevik Onar, Sezi. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1326267
700 1 $a Cebi, Selcuk. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1320431
700 1 $a Kahraman, Cengiz. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 682908
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030856250
776 0 8 $i Printed edition: $z 9783030856274
830 0 $a Lecture Notes in Networks and Systems, $x 2367-3370 ; $v 1 $3 1267315
856 4 0 $u https://doi.org/10.1007/978-3-030-85626-7
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)