Details

Linguistic Decision Making

Numerical Scale Model and Consistency-Driven Methodology

von: Yucheng Dong, Jiuping Xu
96,29 €
Verlag:	Springer
Format:	PDF
Veröffentl.:	11.12.2018
ISBN/EAN:	9789811329166
Sprache:	englisch

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Beschreibungen

Titelbeschreibung

This book proposes a novel CWW model to personalize individual semantics in linguistic decision making, based on two new concepts: numerical scale and consistency-driven methodology. The numerical scale model provides a unified framework to connect different linguistic symbolic computational models for CWW, and the consistency-driven methodology customizes individuals’ semantics to support linguistic group decision making by setting personalized numerical scales. The book is a valuable resource for researchers and postgraduates who are interested in CWW in linguistic decision making.

Inhaltsverzeichnis

1 Introduction <div>1.1 Computing with words in decision making </div><div>1.2 Linguistic symbolic computational models </div><div>1.2.1 The 2-tuple linguistic model </div><div>1.2.2 The proportional 2-tuple linguistic model </div><div>1.2.3 Linguistic hierarchy </div><div>1.2.4 Hesitant linguistic term set </div><div>1.3 A core problem in linguistic decision making </div><div>References </div><div>2 Numerical scale model </div><div>2.1 Numerical scale </div><div>2.1.1 The definition of numerical scale </div><div>2.1.2 Interval numerical scale </div><div>2.2 Linguistic computational model </div><div>2.2.1 Linguistic computational framework </div><div>2.2.2 Linguistic aggregation </div><div>2.2.3 Illustrative example </div><div>2.3 Setting the interval numerical scale based on IT2 FSs </div><div>2.3.1 Generalizing the Wang and Hao model </div><div>2.3.2 Comparative study </div><div>References </div><div>3 A unified framework </div>3.1 Connecting numerical scale model to linguistic hierarchy <div>3.1.1 Definition of unbalanced linguistic term sets </div><div>3.1.2 The revised retranslation process in linguistic hierarchy </div><div>3.1.3 Equivalence between numerical scale model and linguistic hierarchy </div>3.2 Hesitant unbalanced linguistic information <div>3.2.1 Possibility degree formulas </div><div>3.2.2 Unbalanced hesitant linguistic aggregation </div><div>References </div><div>4 Consistency of interval-like reciprocal preference relations </div><div>4.1 Consistency of interval-valued reciprocal preference relations </div><div>4.1.1 Interval-valued reciprocal preference relations </div><div>4.1.2 Average-case consistency measure </div><div>4.1.3 Average-case consistency improving method </div><div>4.2 Consistency of hesitant linguistic preference relations </div><div>4.2.1 Hesitant linguistic preference relations </div><div>4.2.2 Interval consistency measure </div><div>4.2.3 Interval consistency measure VS Normalization method </div><div>4.2.4 Connection among ICI, NCI, and ACI </div><div>References </div><div>5 Consistency-driven methodology </div><div>5.1 Personalized individual semantics in linguistic term sets </div><div>5.1.1 Consistency-driven methodology to set personalized interval numerical scales </div><div>5.1.2 A CWW framework with PISs </div><div>5.2 Personalized individual semantics in hesitant linguistic contexts  </div><div>5.2.1 Personalizing hesitant individual semantics </div><div>5.2.2 Numerical examples and analysis </div><div>5.2.3 Discussion: Advantages and limitations </div><div>References </div><div>6 Applications in various decision problems </div><div>6.1 The analytic hierarchy process </div>6.1.1 Basic knowledge <div>6.1.2 The framework of the AHP with PISs </div><div>6.1.3 Consistency-driven methodology to deal with PISs </div><div>6.1.4 Personalized AHP interval numerical scales </div><div>6.2 Consensus model in linguistic GDM problem </div><div>6.2.1 A GDM framework with PISs </div><div>6.2.2 Consensus reaching process </div><div>6.3 MAGDM with linguistic preference information on alternatives </div><div>6.3.1 MAGDM with numerical preference information </div><div>6.3.2 A PIS based MAGDM framework </div><div>6.3.3 Obtaining the individual numerical scales with PISs </div><div>6.3.4 Numerical and simulation analysis </div><div>References</div>

Autorenportrait

<div><b>Yucheng Dong</b> is a Professor at the Business School of Sichuan University, China. His current research interests include linguistic decision making, group decision making, opinion dynamics, social network decision making. He is the author or coauthor of over 90 refereed articles published in international journals, a member of the editorial board of <i>Information Fusion</i> and the area editor of <i>Computers and Industrial Engineering</i>.</div><div><br></div><div><b>Jiuping Xu</b> is a Cheung Kong Professor at the Business School of Sichuan University, China. He has published over 40 books, and he is the author or coauthor of more than 200 refereed articles published in international journals. Dr. Xu is the President of the International Society for Management Science and Engineering Management, and the Editor-in-Chief of the International Journal of <i>Management Science and Engineering Management</i>.</div>

Back cover copy

Sonderbeitrag

<p>The first book to use the numerical scale model and consistency-driven methodology to support linguistic decision making</p><p>Provides a comprehensive and accessible guide to different linguistic computational models</p><p>Enables researchers to understand the connection between various linguistic computational models</p><p>Provides researchers with a new way to deal with the fact that words mean different things for different people or in different contexts</p>