Artificial intelligence in project management and making decisions / Pedro Y. Piñero Pérez, Rafael E. Bello Pérez and Janusz Kacprzyk, editors.

Format:

Book

Contributor:

Piñero Pérez, Pedro Y., editor.

Bello Pérez, Rafael E., editor.

Kacprzyk, Janusz, editor.

Series:

Studies in computational intelligence ; Volume 1035.

Studies in computational intelligence ; Volume 1035

Language:

English

Subjects (All):

Artificial intelligence.

Project management--Data processing.

Project management.

Project management--Decision making.

Physical Description:

1 online resource (423 pages)

Place of Publication:

Cham, Switzerland : Springer, [2022]

Summary:

This book presents new developments and advances in the theory, applications, and design methods of computational intelligence, integrated in various areas of project management and BIM environments. The chapters of the book span different soft computing techniques, such as: linguistic data summarization, fuzzy systems, evolutionary algorithms, estimation distribution algorithms, computing with words, augmented reality, and hybrid intelligence systems. In addition, different applications of the neutrosophic theory are presented for the treatment of uncertainty and indeterminacy in decision-making processes. Several chapters of the book constitute systematic reviews, useful for future investigations in the following topics: linguistic summarization of data, augmented reality, and the development of BIM technologies. It is a particularly interesting book for engineers, researchers, specialists, teachers, and students related to project management and the development of BIM technologies.

Contents:

Intro

Preface

Acknowledgments

Contents

Part I Linguistic Data Summarization for Decision-Making in Project Management

1 Linguistic Data Summarization: A Systematic Review

1 Introduction

2 Methodology

3 Linguistic Data Summarization Review

3.1 Evolution and Trends in Protoforms for the Construction of Summaries

3.2 Methods or Techniques for the Generation of Linguistic Data Summaries

3.3 Main Validation Techniques and Methods Used in the Investigations

3.4 Areas of Application of Linguistic Summaries

4 Conclusions

References

2 New Linguistic Data Summarization Approach for Prediction Problems in Project Management Applications

2 Structure of Linguistic Summaries and Contact Points with Fuzzy Inference Systems

3 A New Approach for Inference Based on Linguistic Summaries

4 Application in Decision-Making in Project Management

4.1 Results of Test 1 Impact of the Use of Different Combinations of T Indicators in the Inference Process

4.2 Results of Test 2 Comparison of the Proposal with Other Inference Methods

5 Conclusions

3 Linguistic Data Summarization with Multilingual Approach

2 New Approach for Linguistic Summaries Generation by Using Controller Natural Language

2.1 Definition of Controlled Natural Languages for the Construction of Multilingual Linguistic Summaries

3 New Algorithms for Generation of Multilingual Linguistic Summaries

3.1 LPALDS Algorithm Based on Probabilistic Graphs

3.2 Algorithm for the Generation of Linguistic Summaries Based on Rough Sets (RSTLDS)

3.3 Algorithm for the Humanization of Linguistic Summaries Using Controlled Natural Languages.

4 Analysis of Results and Validation of the Proposed Algorithms

4.1 Comparison of the Proposed Algorithms with Others Reported in the Bibliography.

4.2 Validation of the Algorithms in Their Ability to Generate Summaries Under a Multilingual Approach

4 Project to Improve Offensive Phase Finalization of Futsal Teams by Using Linguistic Data Summarization Techniques

2 Discovering Linguistic Summaries Deal with Futsal Team Weaknesses

3 Results and Discussion

3.1 Variable Goal in the 2018/2019 Seasons

3.2 Variable Positive Shots in 2018/2019 Seasons

3.3 Static Positional Strategy Plays in 2018/2019 Seasons with Respect to Goal and Positive Shots

3.4 Positional Transitions in Motion in 2018/2019 Seasons Regarding Goal and Positive Shots

5 Algorithms for Linguistic Description of Categorical Data

2 Method for Generating Composite Linguistic Summaries

2.1 Generation of Association Rules

2.2 Building Type-I Constituent Summaries

2.3 Building Type-II Constituent Summaries

2.4 Building the Evidence Composite Relations

2.5 Building the Contrast Composite Relations

2.6 Building the Emphasis Composite Relations

3 Use Case

3.1 Design and Implementation

3.2 Results and Examples

4 Evaluating the Interpretability of Relations

4.1 Design

4.2 Instrument

5 Results and Discussion

6 Conclusions

6 New Indicators for the Assessment of Linguistic Summaries Considering a Rough Sets Approach

2 Traditional Indicators for the Evaluation of Linguistic Summaries

2.1 Degree of Truth

2.2 Degree of Imprecision T2

2.3 Degree of Coverage T3

2.4 Degree of Appropriateness T4

2.5 Length of a Summary T5

3 New Extensions of T Indicators to Evaluate Linguistic Summaries

3.1 Definitions and Notations Used in the Proposed Extensions

3.2 Extensions for Calculating the Degree of Truth Te1a.

3.3 Extensions to Degree of Imprecision

3.4 Extension to the Calculation of the Degree of Coverage Te3

3.5 Extension to the Calculation of the Degree of Appropriateness Te4

3.6 Extension to the Evaluation of the Length of Te5 Summaries

4 Comparison of Traditional and Extended Indicators

4.1 Analysis of the Behavior of the Degree of Truth Indicator and Its Extensions

4.2 Analysis of the Behavior of the Degree of Support Indicator and Its Extension

4.3 Analysis of the Behavior of the Degree of Appropriateness Indicator and Its Extension

4.4 Analysis of the Behavior of the Indicator Length of a Summary and Its Extension

4.5 Summary of Comparison of Indicators Regarding the Treatment of Uncertainty

Part II Planning and Sustainability of Projects Assisted by Artificial Intelligence

7 Constraints Learning Univariate Estimation of Distribution Algorithm on the Multi-mode Project Scheduling Problem

2 Modeling the MMRCPSP Optimization Problem

2.1 Formalization of the Optimization Problem

2.2 Constraints Learning Univariate Marginal Distribution Algorithm (CLUMDA)

2.3 Solution Design

2.4 Detailed Formalization of the CLUMDA

3 Experimental Results and Discussion

3.1 "Mean Makespan" Variable

3.2 "Number of Times the Optimum Founded" Variable

8 New Methods for Feasibility Analysis of Investment Projects in Uncertain Environments

2 Background

3 Model for the Feasibility Analysis of Investment Projects in Environments with Uncertainty

4 Experimentation

4.1 Case Study

9 Sustainability Risk Management for Project-Oriented Organizations

2 Procedure

2.1 Stage 1. Previous Preparation

2.2 Stage 2. Organizational Analysis.

2.3 Stage 3. Risk Evaluation

2.4 Stage 4. Risk Treatment

2.5 Stage 5. Monitoring and Continuous Improvement

3 Results

3.1 User Satisfaction with the Proposed Procedure

3.2 Case Study

10 New Extensions of Fuzzy Cognitive Maps for Sequential Multistage Decision-Making Problems: Application in Project Management

2 Multistage Sequential Triangular Neutrosophic Cognitive Map (MSTrNCM)

2.1 Representation of the Relationships Among Concepts and Map Construction

2.2 Map Inference and Activation Function

3 Neutrosophic Cognitive Map Based on Linguistic Data Summarization

3.1 Representation of the Relationships Among Concepts and Map Construction

3.2 Inference Process of NCMLDS

4 Validation and Results Analysis

4.1 Experiment 1: Analysis of the Algorithms Regarding the Parameter Lambda Λ

4.2 Experiment 2: Comparison Regarding the Error in Prediction and Precision

4.3 Experiment 3: Algorithms Applicability Analysis

4.4 Experiment 4: Evaluation of the Efficiency of Algorithms Considering the Indicator "Execution Time"

5 Conclusion and Future Work

11 A Software Ecosystem for Project Management in BIM Environments Assisted by Artificial Intelligent Techniques

2 Brief Analysis of Software Ecosystems

3 Architecture of the BusinessRedmine Software Ecosystem

4 Results Analysis

4.1 Experiment 1: Comparison of the Proposal with Other Tools

4.2 Experiment 2: Analysis of the System Implementation Process in Different Scenarios

4.3 Experiment 3: Analysis of the Behavior of the Project Evaluation Subsystem

Part III Knowledge and Human Resources Management Assisted by Artificial Intelligence

12 Team Formation Integrating Various Factors: Model and Solution Approach

1 Introduction.

2 Related Works

2.1 Formation of Student Teams

2.2 Formation of Experts Teams in Social Networks

2.3 Formation of Sports Teams

2.4 Formation of Professional Teams

2.5 Formation of Software Teams

2.6 Formation of Medical Teams

3 Multiple Team Formation Model

4 Solution Approach to the Multiple Team Formation Model

5 Experiments

6 Conclusions and Future Works

13 A TOPSIS-Based Method for Personnel Selection in Software Projects

2 Background on MCDM Process and Methods

3 The Proposed TOPSIS-Based Method for Personnel Selection in Software Projects

4 Solving a Personnel Selection Problem in a Cuban IT Project

14 Combining Artificial Intelligence and Project Management Techniques in Ecosystem for Training and Innovation

2 Proposal for an Ecosystem of Training and Innovation in Project Management

3 Analysis of Results and Application of the Program

3.1 Analysis of Results in the Application in the Master's Program in Project Management

3.2 Analysis of Results in the Development of the BusinessRedmine Ecosystem and Its Application in Different Environments

15 Evaluation of an Accreditation Variable for University Institutions Using 2 Tuple Linguistic Representation Model

2 Materials and Methods

2.1 Characteristics of the Quality Evaluation Process of Higher Education Institutions in Cuba

2.2 The Evaluation of the Quality of HEIs as a Decision-Making Problem

3.1 Description and Classification of the Problem

3.2 Solution of the Problem by Means of FLINSTONES

16 Ontology-Based Management of the Scientific Activity in Software Development Projects

2 Technologies and Tools.

3 Ontology for the Management of Scientific Activity.

Notes:

Includes bibliographical references.

Description based on print version record.

ISBN:

3-030-97269-0