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

• Record Nr.: UNINA9910559383303321
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2022]; ©2022
• ISBN: 3-030-97269-0
• Descrizione fisica: 1 online resource (423 pages)
• Collana: Studies in computational intelligence ; ; Volume 1035
• Disciplina: 006.3
• Soggetti: Artificial intelligence; Project management - Data processing; Project management - Decision making
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: 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 -- 1 Introduction -- 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 -- References -- 3 Linguistic Data Summarization with Multilingual Approach -- 1 Introduction -- 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 -- 5 Conclusions -- References -- 4 Project to Improve Offensive Phase Finalization of Futsal Teams by Using Linguistic Data Summarization Techniques -- 1 Introduction -- 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 -- 4 Conclusions -- References -- 5 Algorithms for Linguistic Description of Categorical Data -- 1 Introduction -- 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 -- References -- 6 New Indicators for the Assessment of Linguistic Summaries Considering a Rough Sets Approach -- 1 Introduction -- 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 -- 5 Conclusions -- References -- 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 -- 1 Introduction -- 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 -- 4 Conclusions -- References -- 8 New Methods for Feasibility Analysis of Investment Projects in Uncertain Environments -- 1 Introduction -- 2 Background -- 3 Model for the Feasibility Analysis of Investment Projects in Environments with Uncertainty -- 4 Experimentation -- 4.1 Case Study -- 5 Conclusions -- References -- 9 Sustainability Risk Management for Project-Oriented Organizations -- 1 Introduction -- 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 -- 4 Conclusions -- References -- 10 New Extensions of Fuzzy Cognitive Maps for Sequential Multistage Decision-Making Problems: Application in Project Management -- 1 Introduction -- 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 -- References -- 11 A Software Ecosystem for Project Management in BIM Environments Assisted by Artificial Intelligent Techniques -- 1 Introduction -- 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 -- 5 Conclusions -- References -- 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 -- References -- 13 A TOPSIS-Based Method for Personnel Selection in Software Projects -- 1 Introduction -- 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 -- 5 Conclusions -- References -- 14 Combining Artificial Intelligence and Project Management Techniques in Ecosystem for Training and Innovation -- 1 Introduction -- 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 -- 4 Conclusions -- References -- 15 Evaluation of an Accreditation Variable for University Institutions Using 2 Tuple ; Linguistic Representation Model -- 1 Introduction -- 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 Results and Discussion -- 3.1 Description and Classification of the Problem -- 3.2 Solution of the Problem by Means of FLINSTONES -- 4 Conclusions -- References -- 16 Ontology-Based Management of the Scientific Activity in Software Development Projects -- 1 Introduction -- 2 Technologies and Tools.; 3 Ontology for the Management of Scientific Activity.