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001453048 001__ 1453048
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001453048 019__ $$a1346535424$$a1347023357
001453048 020__ $$a9783031082467$$q(electronic bk.)
001453048 020__ $$a303108246X$$q(electronic bk.)
001453048 020__ $$z9783031082450
001453048 020__ $$z3031082451
001453048 0247_ $$a10.1007/978-3-031-08246-7$$2doi
001453048 035__ $$aSP(OCoLC)1347270821
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001453048 08204 $$a658.403028563$$223/eng/20221012
001453048 24500 $$aHandbook on decision making.$$nVolume 3,$$pTrends and challenges in intelligent decision support systems /$$cedited by Julian Andres Zapata-Cortes, Cuauhtémoc Sánchez-Ramírez, Giner Alor-Hernández, Jorge Luis García-Alcaraz.
001453048 24630 $$aTrends and challenges in intelligent decision support systems
001453048 264_1 $$aCham :$$bSpringer,$$c[2023]
001453048 300__ $$a1 online resource (1 volume) :$$billustrations (black and white, and color).
001453048 336__ $$atext$$btxt$$2rdacontent
001453048 337__ $$acomputer$$bc$$2rdamedia
001453048 338__ $$aonline resource$$bcr$$2rdacarrier
001453048 4901_ $$aIntelligent systems reference library ;$$vvolume 226
001453048 504__ $$aIncludes bibliographical references.
001453048 5050_ $$aIntro -- Preface -- Acknowledgements -- Contents -- Contributors -- Part I Methods and Techniques -- 1 A Vertical Fragmentation Method for Multimedia Databases Considering Content-Based Queries -- 1.1 Introduction -- 1.2 Background -- 1.3 State of the Art -- 1.4 Design of CBRVF -- 1.4.1 CBRVF -- 1.4.2 Web Application Design -- 1.5 Results and Discussion -- 1.6 Conclusion and Future Work -- References -- 2 An Approach Based on Process Mining Techniques to Support Software Development -- 2.1 Introduction -- 2.2 Background -- 2.3 Related Work -- 2.4 Framework
001453048 5058_ $$a2.4.1 Phase 1: Event Log Management -- 2.4.2 Phase 2: Process Model Discovery -- 2.4.3 Phase 3: Statistics -- 2.5 Results -- 2.5.1 Case of a Purchase Order Process -- 2.5.2 Case of an Air Quality Monitoring System Process -- 2.6 Conclusions -- References -- 3 Analysis of Canonical Heuristic Methods for the Optimization of an Investment Portfolio -- 3.1 Introduction -- 3.2 Evolutionary Algorithms -- 3.3 Investment Portfolio -- 3.4 Theoretical Scaffolding -- 3.5 Genetic Algorithm -- 3.6 Differential Evolution -- 3.7 Artificial Immunological System -- 3.8 Methodology -- 3.9 Results
001453048 5058_ $$a3.10 Conclusions -- References -- 4 Design of a Dynamic Horizontal Fragmentation Method for Multimedia Databases -- 4.1 Introduction -- 4.2 Background -- 4.3 Related Works -- 4.4 Design of a Dynamic Horizontal Fragmentation Method for Multimedia Databases -- 4.5 Results and Discussion -- 4.6 Conclusion -- References -- 5 Efficient Archiving Method for Handling Preferences in Constrained Multi-objective Evolutionary Optimization -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Multi-objective Evolutionary Algorithms -- 5.3.1 Algorithms of Multi-Objective Evolutionary Optimization
001453048 5058_ $$a5.3.2 Preference-Based MOEAs -- 5.3.3 Assessing Performance -- 5.4 Proposal -- 5.4.1 Archiving Regions of Interest -- 5.5 Experimental Step -- 5.5.1 Problems to Be Solved -- 5.5.2 Algorithms for Comparison -- 5.5.3 Parameter Settings -- 5.6 Results and Discussion -- 5.6.1 Results on Unconstrained Problems (DTLZ) -- 5.6.2 Results on Constrained Problems (C-DTLZ) -- 5.6.3 Results on Real-World Multi-Objective Problems -- 5.7 Conclusions and Future Work -- References -- 6 Evaluation of Machine Learning Techniques for Malware Detection -- 6.1 Introduction -- 6.2 Related Work -- 6.3 Background
001453048 5058_ $$a6.3.1 Machine Learning Techniques -- 6.3.2 Measurement -- 6.4 Methodology -- 6.4.1 Data Preprocessing -- 6.4.2 Data Representation -- 6.4.3 Model Training/Testing -- 6.5 Results -- 6.5.1 Data Sets -- 6.5.2 Performance -- 6.6 Conclusions -- References -- 7 Implementation of Reinforcement-Learning Algorithms in Autonomous Robot Navigation -- 7.1 Introduction -- 7.2 Systematic Review of the Literature -- 7.2.1 Heuristic Algorithms -- 7.2.2 Applications of Reinforcement Learning -- 7.2.3 Synthesis and Considerations -- 7.3 Characteristics of Reinforcement Learning Algorithms -- 7.4 Methodology
001453048 506__ $$aAccess limited to authorized users.
001453048 520__ $$aThis book presents different techniques and methodologies used to improve the intelligent decision-making process and increase the likelihood of success in companies of different sectors such as Financial Services, Education, Supply Chain, Energy Systems, Health Services, and others. The book contains and consolidates innovative and high-quality research contributions regarding the implementation of techniques and methodologies applied in different sectors. The scope is to disseminate current trends knowledge in the implementation of artificial intelligence techniques and methodologies in different fields such as: Logistics, Software Development, Big Data, Internet of Things, Simulation, among others. The book contents are useful for Ph.D. researchers, Ph.D. students, master and undergraduate students of different areas such as Industrial Engineering, Computer Science, Information Systems, Data Analytics, and others.
001453048 588__ $$aDescription based on print version record.
001453048 650_0 $$aDecision making$$xData processing.
001453048 650_0 $$aArtificial intelligence$$xIndustrial applications.
001453048 655_0 $$aElectronic books.
001453048 7001_ $$aZapata-Cortes, Julian Andres,$$eeditor.
001453048 7001_ $$aSanchez-Ramirez, Cuauhtemoc,$$d1976-$$eeditor.
001453048 7001_ $$aAlor-Hernández, Giner,$$d1977-$$eeditor.$$1https://isni.org/isni/000000043678904X
001453048 7001_ $$aGarcía-Alcaraz, Jorge Luis,$$eeditor.$$1https://isni.org/isni/0000000443394126.
001453048 77608 $$iPrint version:$$tHandbook on decision making. Volume 3, Trends and challenges in intelligent decision support systems.$$dCham : Springer, 2022$$z9783031082450$$w(OCoLC)1338676795
001453048 830_0 $$aIntelligent systems reference library ;$$vv. 226.
001453048 852__ $$bebk
001453048 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-08246-7$$zOnline Access$$91397441.1
001453048 909CO $$ooai:library.usi.edu:1453048$$pGLOBAL_SET
001453048 980__ $$aBIB
001453048 980__ $$aEBOOK
001453048 982__ $$aEbook
001453048 983__ $$aOnline
001453048 994__ $$a92$$bISE