Decision-making with neutrosophic set : theory and applications in knowledge management / Harish Garg, editor.

Format:

Book

Contributor:

Garg, Harish, editor.

Series:

Computational Mathematics and Analysis

Language:

English

Subjects (All):

Neutrosophic logic.

Physical Description:

1 online resource (402 pages)

Place of Publication:

New York : Nova Science Publishers, [2021]

Summary:

"This book introduces readers to the concept of the neutrosophic set which can deal with dynamic and complex decision-making problems. With the complexity of the socio-economic environment, today's decision-making is one of the most notable ventures, whose mission is to decide the best alternative under numerous known or unknown criteria. This book provides a large amount of theoretical and practical information about the latest research in the field, allowing readers to gain an extensive understanding of both the fundamentals and applications of neutrosophic sets to solve different kinds of decision-making problems and mathematical programming such as medical diagnosis, pattern recognition, construction problems, technology selection etc."-- Provided by publisher.

Contents:

Intro

Contents

Preface

Section I: Mathematical Aspects of Neutrosophic Set

Chapter 1

Neutrosophic Set Theory and

Engineering Applications: A Study

Abstract

1. Introduction

1.1. Types of Neutrosophic Set

Interval Valued Neutrosophic Set

Fuzzy Neutrosophic Set

Intuitionistic Neutrosophic Set

Single Valued Neutrosophic Set

Bipolar Neutrosophic Set

1.2. Neutrosophic Set Operations

Containment

Complement

Union

Intersection

Product

Addition

Subtraction

Equality

Inclusion

Division

2. Terminologies

3. Neutrospophic Set Applications in Civil Engineering

Property-1

Applicability

Description

Usefulness

Property-2

Property-3

Illustration of Interval Value Based Analysis of Efficiency Achieved by the Neutrosophic Based Civil Engineering

4. Neutrospophic Set Applications in Aeroscape Engineering

Illustration of Interval Value Based Analysis of Efficiency Achieved by the Neutrosophic Based Aerospace Engineering

5. Neutrospophic Set Applications in Mechanical Engineering

Illustration of Interval Value Based Analysis of Efficiency Achieved

by the Neutrosophic Based Mechanical Engineering

Conclusion

References

Chapter 2

A New Type of Quasi Open Functions in Neutrosophic Topological Environment

Chapter 3

Accordance with Neutrosophic Logic? A Multimoora Approach for Countries Worldwide.

1. The Credit Rating of Firms

Companies Do they Work Scientifically?

2. Choice of Objectives (Criteria) Characterizing the Economies of the Countries

3. A Choice of a Method for the Multi-Objective Optimization of the Rating of Countries

3.1. Neutrosophic False

3.2. Neutrosphic True

3.3. Multi-Objective Optimization by Ratio Analysis (MOORA)

3.3.1. The First Part of MOORA: The Ratio Analysis

3.3.2. The Second Part of MOORA with the Reference Point

3.4. MULTIMOORA

3.5. The Theory of Ordinal Dominance

3.5.1. Axioms on Ordinal and Cardinal Scales

3.5.2. Dominance, being Dominated, Transitiveness and Equability

Dominance

Transitiveness

Overall Dominance of One Alternative on Another

Equability

4. Indeterminacy towards Neutrosophic Philosophy

4.1. The Liquidity of a Country being its Capacity to pay Debts on Time Due

4.1.1. No Public Debt in Other Currencies

2. Difference between External and Internal Public Debt

3. The Reserves of the Central Bank

4. The Money Machine

4.2. The Solvency of a Country

5. Points Still to be Discussed

5.1. The Importance of Each Objective or Criterion

5.1.1. Multiplication with a Coefficient of Importance (False after Neutrosphic Logic)

5.1.2. Adding a Number to an Objective (False after Neutrosphic Logic)

5.1.3. Multiplying an Objective with an Exponent

5.1.4. Dividing an Objective in Different Sub-Objectives

(True after Neutrosphic Logic)

5.2. All Stakeholders

5.3. The Choice of Objectives (Criteria)

5.4. The Choice of Solutions

6. Final Classification of the Countries by MULTIMOORA and Ordinal Dominance

6.1. Previous Studies

6.2. Comparison with Standard &amp

Poor's Rates 2020

6.2. Missing Countries

6.3. Luxemburg: Another Exception

6.4. Another Hot Issue: Ireland

6.5. The United Kingdom.

6.6. The United States

7. Economic Capability per Country: A Method of Forecasting?

7.1. The Necessity to Come to a Structural Credit Rating System for Countries Based on Continuity

7.2. S&amp

P's and Forecasting

Acknowledgments

Appendix B.

Appendix C. Share of Pollution for Lithuanian Counties 2002

Chapter 4

Evaluation of Online Education Software under Neutrosophic Environment

2. Neutrosophic Sets

Preliminaries of the Single Valued Neutrosophic Set

Definition 1

Definition 2

Definition 3

Definition 4

Definition 5

Definition 6

Definition 7

Definition 8

3. Neutrosophic MULTIMOORA Method

3.1. Neutrosophic MOORA- Ratio Method

3.2. Neutrosophic Moora-Reference Point Method

3.3. Neutrosophic MOORA-Full Multiplicative Form

3.4. Dominance Theory

4. Application

Neutrosophic MOORA- Ratio Method

Neutrosophic Moora-Reference Point Method

Neutrosophic MOORA-Full Multiplicative Form

Dominance Theory

5. Sensitivity Analysis

6. Comparative Analysis

Algorithm 1. Pseudo Representation of NS-TOPSIS

Chapter 5

A New Attribute Sampling Plan for Assuring Weibull Distributed Lifetime using Neutrosophic Statistical Interval Method

2. Designing of Sampling Plan under Weibull Distribution Using Neutrosophic Statistics

3. Application of the Proposed Plan

4. Comparative Study

Section II: Decision Making Problems with Neutrosophic Set

Chapter 6

On Some Propositions of Boundary in Interval Valued Neutrosophic Bitopological Space

2. Basic Operations

Definition 2.1. [18]

Definition 2.2. [18]

Definition 2.3. [18]

Definition 2.4. [18].

Definition 2.5. [18]

Definition 2.6. [22]

Definition 2.7. [7]

Definition 2.8. [7]

3. Main Results

Definition 3.1.

Example 3.1.

Definition 3.2.

Example 3.2.

Theorem 3.1.

Remark 3.1.

Example 3.3.

Definition 3.3.

Example 3.4.

Theorem 3.2.

Remark 3.2.

Example 3.5.

Theorem 3.3.

Definition 3.4.

Proposition 3.1.

Remark 3.3.

Example 3.6.

Proposition 3.2.

Remark 3.4.

Example 3.7.

Proposition 3.3.

Example 3.8.

Proposition 3.4.

Example 3.9.

Remark 3.5.

Example 3.10.

Proposition 3.6.

Remark 3.6.

Proposition 3.7.

Remark 3.7.

Example 3.12.

Proposition 3.9.

Chapter 7

An Expected Value-Based Novel Similarity Measure for Multi-Attribute Decision-Making Problems with Single-Valued Trapezoidal Neutrosophic Numbers

1.1. Existing Research Gap

1.2. Motivation of the Work

1.3. Structure of the Paper

2. Basic Preliminaries

3. Expected Value of a SVTNN and the Proposed SM Approach

3.1. Expected Value Calculation

3.2. Proposed SM Approach

3.3. Validity and Superiority of the Proposed SM Approach

4. MADM under SVN Environment

4.1. Formulate the Decision Matrix

4.2. Standardize the Decision Matrix

4.3. Determining the Ideal Solution According to the Attribute Type

4.4. Evaluate the Similarity Measure Values

4.5. Ranking of the Alternatives

5. Numerical Illustration

5.1. Comparative Study

Conflict of Interest

Ethical Approval

Chapter 8

TrNN-ARAS Strategy for Multi-Attribute Group Decision-Making (MAGDM) in Trapezoidal Neutrosophic Number Environment with Unknown Weight

1.1. Motivation of the Work

1.2. Research Methodology

1.3. Research Contribution.

2. Literature Review

3. Preliminaries

4. Entropy Measure for TrNNs

4.1. Determination of the Unknown Weights of the Decision Makers and Weights of the Criteria Using the Proposed Entropy Measure

5. Extended ARAS Strategy for MAGDM in TrNNs Environment

6. Numerical Example

7. Comparative Analysis

8. Advantages of the Proposed Strategy Compare to VIKOR Strategy

Conclusion and Future Research Direction

Chapter 9

An Application of Reduced Interval Neutrosophic Soft Matrix in Medical Diagnosis

2.Preliminaries

2.1. Definition [41]

2.2. Definition [1]

2.3. Definition [15]

2.4. Definition [2]

2.5. Definition [35]

2.6. Definition [37]

2.7. Example

2.8. Definition [25]

2.9. Definition [16]

2.10. Definition [32]

2.11. Definition [21]

2.12. Example

3. Interval Neutrosophic Soft Matrices

3.1. Definition

3.2. Definition

3.3. Definition

3.4. Definition

3.5. Definition

3.6. Definition

3.7. Definition

3.8. Example

3.9. Definition

3.10. Example

3.11. Definition

3.12. Example

3.13. Definition

3.14. Example

3.15. Definition

4. Decision Making Problem by Using the Interval Neutrosophic Soft Sets for Medical Diagnosis

Algorithm

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

Step 8

5. Application of Interval Neutrosophic Soft Matrices in Medical Diagnosis

Chapter 10

Interval-Valued Neutrosophic N Soft Set and Intertemporal Interval-Valued Neutrosophic N Soft Set to Assess the Resilience of the Workers Amidst Covid-19

Section III. Extension of the Neutrosophic Set

Chapter 11.

2-Additive Choquet Cosine Similarity Measures for Simplified Neutrosophic Sets and Applications to Medical Diagnosis.

Notes:

Description based on print version record.

ISBN:

1-5361-9522-7

OCLC:

1250088989