Fuzzy sets and systems II

  • Teaching

    Details

    Faculty Faculty of Science and Medicine
    Domain Computer Science
    Code UE-SIN.08620
    Languages English
    Type of lesson Lecture
    Level Master
    Semester SP-2023

    Schedules and rooms

    Summary schedule Friday 14:15 - 17:00, Hebdomadaire (Spring semester)
    Struct. of the schedule 3h par semaine durant 14 semaines
    Contact's hours 42

    Teaching

    Responsibles
    • Portmann Edy
    Teachers
    • Portmann Edy
    Assistants
    • Nguyen Minh Tue
    Description

    The idea of this lecture series is to introduce students into fuzzy modelling methods. With today’s information overload, it has become increasingly difficult to analyze the huge amounts of data and to generate appropriate management decisions. Furthermore, the data are often imprecise and will include both quantitative and qualitative elements. For these reasons it is important to extend traditional decision making processes by adding intuitive reasoning, human subjectivity and imprecision.

    To deal with uncertainty, vagueness, and imprecision, Lotfi A. Zadeh introduced fuzzy sets and fuzzy logic. In this series fuzzy logic is applied to extend and model portfolio analysis, scoring methods, customer relationship management, performance measurement, web reputation, web analytics and controlling, community marketing and other business domains to improve managerial decisions. Thus, fuzzy logic can be seen as a modeling and management method where appropriate concepts, software tools and languages build a powerful instrument for analyzing and controlling the business.

    Training objectives

    On successful completion of this lecture series, the students will have…
    - …learned about key fuzzy management methods applied to business, government and society.
    - …become familiar with development methods within a small group to model and implement a fuzzy application.
    - …modeled and presented a state-of-the-art fuzzy application.

    Comments

    MSc-CS BENEFRI - (Code Ue: 53104 Track: T5 , Code Ue: 63104 Track. T6) The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/.

    Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/

    Softskills No
    Off field No
    BeNeFri Yes
    Mobility Yes
    UniPop No
  • Dates and rooms
    Date Hour Type of lesson Place
    24.02.2023 14:15 - 17:00 Cours PER 21, Room F130
    03.03.2023 14:15 - 17:00 Cours PER 21, Room F130
    10.03.2023 14:15 - 17:00 Cours PER 21, Room F130
    17.03.2023 14:15 - 17:00 Cours PER 21, Room F130
    24.03.2023 14:15 - 17:00 Cours PER 21, Room F130
    31.03.2023 14:15 - 17:00 Cours PER 21, Room F130
    21.04.2023 14:15 - 17:00 Cours PER 21, Room F130
    28.04.2023 14:15 - 17:00 Cours PER 21, Room F130
    05.05.2023 14:15 - 17:00 Cours PER 21, Room F130
    12.05.2023 14:15 - 17:00 Cours PER 21, Room F130
    26.05.2023 14:15 - 17:00 Cours PER 21, Room F130
    02.06.2023 14:15 - 17:00 Cours PER 21, Room F130
  • Assessments methods

    Examen

    Assessments methods By rating
  • Assignment
    Valid for the following curricula:
    Additional Courses in Sciences
    Version: ens_compl_sciences
    Paquet indépendant des branches > Specialized courses in Computer Science (Master level)

    Additional programme requirements for PhD studies [PRE-DOC]
    Version: 2020_1/v_01
    Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Computer Science (Master level)

    Computer Science [3e cycle]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Computer Science (Master level)

    Computer Science [POST-DOC]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Computer Science (Master level)

    MSc in Computer science (BeNeFri)
    Version: 2023_1/V_01
    MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T6: Data Science
    MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T5 : Information Systems and Decision Support

    Ma - Business Communication : Business Informatics - 90 ECTS
    Version: 2020/SA_V02
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Informatik > Data Science
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization

    Ma - Business Informatics - 90 ECTS
    Version: 2020/SA-v01
    Classes - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for Digitalization
    Classes - min. 45 ECTS > Module IT and IT Management > Data Science
    Classes - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization

    MiMa - Business Informatics - 30 ECTS
    Version: 2020/SA_V01
    Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization
    Cours > Module Informatik > Data Science

    MiMa - Data Analytics - 30 ECTS
    Version: 2020/SA-v01
    À choix 9 crédits ECTS > TMD: Technologies and Modelling for Digitalization
    À choix 9 crédits ECTS > Data Science