Modeling and simulating complex business perceptions: using graphical models and fuzzy cognitive maps
Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems. This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a comb...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham, Switzerland
Springer
[2021]
|
| Schriftenreihe: | Fuzzy management methods
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| Schlagworte: | |
| Online-Zugang: | FHD01 |
| Zusammenfassung: | Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems. This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness. Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process |
| Beschreibung: | 1 Online-Ressource (xxv, 154 Seiten) |
| ISBN: | 9783030814960 |
Internformat
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| 490 | 0 | |a Fuzzy management methods | |
| 505 | 8 | |a Chapter 1. Introduction -- Chapter 2. Data Analysis -- Chapter 3. Fuzzy Cognitive Maps -- Chapter 4. Data Modeling -- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures -- Chapter 6. The proposed data-driven glassoFCM method -- Chapter 7. Thesis Conclusions | |
| 520 | |a Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems. This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness. Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process | ||
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Datensatz im Suchindex
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| author | Dikopoulou, Zoumpolia |
| author_facet | Dikopoulou, Zoumpolia |
| author_role | aut |
| author_sort | Dikopoulou, Zoumpolia |
| author_variant | z d zd |
| building | Verbundindex |
| bvnumber | BV047629402 |
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| contents | Chapter 1. Introduction -- Chapter 2. Data Analysis -- Chapter 3. Fuzzy Cognitive Maps -- Chapter 4. Data Modeling -- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures -- Chapter 6. The proposed data-driven glassoFCM method -- Chapter 7. Thesis Conclusions |
| ctrlnum | (OCoLC)1289776064 (DE-599)BVBBV047629402 |
| format | Electronic eBook |
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| id | DE-604.BV047629402 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:45:06Z |
| indexdate | 2024-07-10T09:17:39Z |
| institution | BVB |
| isbn | 9783030814960 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033013846 |
| oclc_num | 1289776064 |
| open_access_boolean | |
| owner | DE-1050 |
| owner_facet | DE-1050 |
| physical | 1 Online-Ressource (xxv, 154 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE FHD01_PQE_Kauf |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | Springer |
| record_format | marc |
| series2 | Fuzzy management methods |
| spelling | Dikopoulou, Zoumpolia Verfasser aut Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps Zoumpolia Dikopoulou Cham, Switzerland Springer [2021] 1 Online-Ressource (xxv, 154 Seiten) txt rdacontent c rdamedia cr rdacarrier Fuzzy management methods Chapter 1. Introduction -- Chapter 2. Data Analysis -- Chapter 3. Fuzzy Cognitive Maps -- Chapter 4. Data Modeling -- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures -- Chapter 6. The proposed data-driven glassoFCM method -- Chapter 7. Thesis Conclusions Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems. This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness. Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process Fuzzy decision making Erscheint auch als Druck-Ausgabe 978-3-030-81495-3 |
| spellingShingle | Dikopoulou, Zoumpolia Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps Chapter 1. Introduction -- Chapter 2. Data Analysis -- Chapter 3. Fuzzy Cognitive Maps -- Chapter 4. Data Modeling -- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures -- Chapter 6. The proposed data-driven glassoFCM method -- Chapter 7. Thesis Conclusions Fuzzy decision making |
| title | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps |
| title_auth | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps |
| title_exact_search | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps |
| title_exact_search_txtP | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps |
| title_full | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps Zoumpolia Dikopoulou |
| title_fullStr | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps Zoumpolia Dikopoulou |
| title_full_unstemmed | Modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps Zoumpolia Dikopoulou |
| title_short | Modeling and simulating complex business perceptions |
| title_sort | modeling and simulating complex business perceptions using graphical models and fuzzy cognitive maps |
| title_sub | using graphical models and fuzzy cognitive maps |
| topic | Fuzzy decision making |
| topic_facet | Fuzzy decision making |
| work_keys_str_mv | AT dikopoulouzoumpolia modelingandsimulatingcomplexbusinessperceptionsusinggraphicalmodelsandfuzzycognitivemaps |