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A Paraconsistent Decision-Making Method

  • Fábio Romeu de Carvalho
  • Jair Minoro Abe

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 87)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 1-16
  3. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 17-35
  4. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 37-40
  5. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 41-56
  6. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 57-70
  7. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 71-148
  8. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 185-191
  9. Fábio Romeu de Carvalho, Jair Minoro Abe
    Pages 193-203
  10. Back Matter
    Pages 205-211

About this book

Introduction

This book presents a novel decision-making support system based on paraconsistent annotated evidential logic, which directly handles imprecise, incomplete and contradictory data. The authors offer insights into areas such as engineering and biomedicine, as well as related fields. Decision analysis is useful in making choices when the consequences of actions are uncertain, like in business administration, where it assists in making investment decisions, and in health care, Decision analysis is also valuable when the possible actions may lead to conflicting consequences. A fundamental tenet of decision analysis is that even though the available information is incomplete, a decision must be made. Thus, analyses often contain assumptions about or estimates of missing data.

The contribution that this method can provide to professionals and companies has significant relevance in terms of the impact of information systems on productivity and quality of the companies; the lack of training companies for proper planning and management of information systems; and the need for interdisciplinary treatment of several sectors of almost all related scientific areas.

This book is a valuable resource for professionals seeking a competitive edge in their performance.

 

Keywords

Decision-making Paraconsistency Incomplete Data Imprecise Data Soft Computing

Authors and affiliations

  • Fábio Romeu de Carvalho
    • 1
  • Jair Minoro Abe
    • 2
  1. 1.Paulista University, UNIPSão PauloBrazil
  2. 2.Paulista University, UNIPSão PauloBrazil

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-74110-9
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-74109-3
  • Online ISBN 978-3-319-74110-9
  • Series Print ISSN 2190-3018
  • Series Online ISSN 2190-3026
  • Buy this book on publisher's site
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