國立高雄大學圖資館 |

Language: English

Back

Fine-Kinney-based fuzzy multi-criter...

Gul, Muhammet.

Fine-Kinney-based fuzzy multi-criteria occupational risk assessmentapproaches, case studies and Python applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fine-Kinney-based fuzzy multi-criteria occupational risk assessmentby Muhammet Gul ... [et al.].
Reminder of title:	approaches, case studies and Python applications /
other author:	Gul, Muhammet.
Published:	Cham :Springer International Publishing :2021.
Description:	xv, 163 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Risk assessmentMathematical models.
Online resource:	https://doi.org/10.1007/978-3-030-52148-6
ISBN:	9783030521486$q(electronic bk.)

Fine-Kinney-based fuzzy multi-criteria occupational risk assessmentapproaches, case studies and Python applications /
Fine-Kinney-based fuzzy multi-criteria occupational risk assessmentapproaches, case studies and Python applications /[electronic resource] :by Muhammet Gul ... [et al.]. - Cham :Springer International Publishing :2021. - xv, 163 p. :ill., digital ;24 cm. - Studies in fuzziness and soft computing,v.3981434-9922 ;. - Studies in fuzziness and soft computing ;v.273..

Fine-Kinney Occupational Risk Assessment Method and its Extensions by Fuzzy Sets: A State of the Art Review -- Fine-Kinney Based Occupational Risk Assessment Using Fuzzy Quality Function Deployment -- Fine-Kinney Based Occupational Risk Assessment Using Interval Type-2 Fuzzy TOPSIS -- Fine-Kinney Based Occupational Risk Assessment Using Interval Valued Pythagorean Fuzzy VIKOR -- Fine-Kinney Based Occupational Risk Assessment Using Intuitionistic Fuzzy TODIM -- Fine-Kinney Based Occupational Risk Assessment Using Hesitant Fuzzy MULTIMOORA -- Fine-Kinney Based Occupational Risk Assessment Using Single Valued Neutrosophic TOPSIS -- Fine-Kinney Based Occupational Risk Assessment Using Interval Type-2 Fuzzy QUALIFLEX -- Fine-Kinney Based Occupational Risk Assessment Using Interval Type-2 Fuzzy VIKOR.

This book presents a number of approaches to Fine-Kinney-based multi-criteria occupational risk-assessment. For each proposed approach, it provides case studies demonstrating their applicability, as well as Python coding, which will enable readers to implement them into their own risk assessment process. The book begins by giving a review of Fine-Kinney occupational risk-assessment methods and their extension by fuzzy sets. It then progresses in a logical fashion, dedicating a chapter to each approach, including the fuzzy best and worst method, interval-valued Pythagorean fuzzy VIKOR and interval type-2 fuzzy QUALIFLEX. This book will be of interest to professionals and researchers working in the field of occupational risk management, as well as postgraduate and undergraduate students studying applications of fuzzy systems.

ISBN: 9783030521486$q(electronic bk.)

Standard No.: 10.1007/978-3-030-52148-6doiSubjects--Topical Terms:

237946
Risk assessment
--Mathematical models.

LC Class. No.: HD61

Dewey Class. No.: 658.155

Fine-Kinney-based fuzzy multi-criteria occupational risk assessmentapproaches, case studies and Python applications /
LDR:02747nmm a2200337 a 4500 001 595007
003 DE-He213
005 20200929184104.0
006 m d
007 cr nn 008maaau
008 211005s2021 sz s 0 eng d
020 $a 9783030521486$q(electronic bk.)
020 $a 9783030521479$q(paper)
024 7 $a 10.1007/978-3-030-52148-6 $2 doi
035 $a 978-3-030-52148-6
040 $a GP $c GP
041 0 $a eng
050 4 $a HD61
072 7 $a TGPR $2 bicssc
072 7 $a TEC032000 $2 bisacsh
072 7 $a TGPR $2 thema
082 0 4 $a 658.155 $2 23
090 $a HD61 $b .F495 2021
245 0 0 $a Fine-Kinney-based fuzzy multi-criteria occupational risk assessment $h [electronic resource] : $b approaches, case studies and Python applications / $c by Muhammet Gul ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xv, 163 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in fuzziness and soft computing, $x 1434-9922 ; $v v.398
505 0 $a Fine-Kinney Occupational Risk Assessment Method and its Extensions by Fuzzy Sets: A State of the Art Review -- Fine-Kinney Based Occupational Risk Assessment Using Fuzzy Quality Function Deployment -- Fine-Kinney Based Occupational Risk Assessment Using Interval Type-2 Fuzzy TOPSIS -- Fine-Kinney Based Occupational Risk Assessment Using Interval Valued Pythagorean Fuzzy VIKOR -- Fine-Kinney Based Occupational Risk Assessment Using Intuitionistic Fuzzy TODIM -- Fine-Kinney Based Occupational Risk Assessment Using Hesitant Fuzzy MULTIMOORA -- Fine-Kinney Based Occupational Risk Assessment Using Single Valued Neutrosophic TOPSIS -- Fine-Kinney Based Occupational Risk Assessment Using Interval Type-2 Fuzzy QUALIFLEX -- Fine-Kinney Based Occupational Risk Assessment Using Interval Type-2 Fuzzy VIKOR.
520 $a This book presents a number of approaches to Fine-Kinney-based multi-criteria occupational risk-assessment. For each proposed approach, it provides case studies demonstrating their applicability, as well as Python coding, which will enable readers to implement them into their own risk assessment process. The book begins by giving a review of Fine-Kinney occupational risk-assessment methods and their extension by fuzzy sets. It then progresses in a logical fashion, dedicating a chapter to each approach, including the fuzzy best and worst method, interval-valued Pythagorean fuzzy VIKOR and interval type-2 fuzzy QUALIFLEX. This book will be of interest to professionals and researchers working in the field of occupational risk management, as well as postgraduate and undergraduate students studying applications of fuzzy systems.
650 0 $a Risk assessment $x Mathematical models. $3 237946
650 0 $a Multiple criteria decision making. $3 219475
650 1 4 $a Quality Control, Reliability, Safety and Risk. $3 274011
650 2 4 $a Python. $3 763308
650 2 4 $a Computational Intelligence. $3 338479
700 1 $a Gul, Muhammet. $3 887157
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in fuzziness and soft computing ; $v v.273. $3 558583
856 4 0 $u https://doi.org/10.1007/978-3-030-52148-6
950 $a Engineering (SpringerNature-11647)