Fuzzy Systems
While several books are available today that address the mathematical and philosophical foundations of fuzzy logic, none, unfortunately, provides the practicing knowledge engineer, system analyst, and project manager with specific, practical information about fuzzy system modeling. Those few books t...
I tiakina i:
| Hōputu: | Online |
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| Reo: | Ingarihi |
| I whakaputaina: |
IntechOpen
2021
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| Ngā marau: | |
| Urunga tuihono: | ONIX_20210420_9789537619923_120 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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| _version_ | 1869519735742267392 |
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| collection | Directory of Open Access Books |
| description | While several books are available today that address the mathematical and philosophical foundations of fuzzy logic, none, unfortunately, provides the practicing knowledge engineer, system analyst, and project manager with specific, practical information about fuzzy system modeling. Those few books that include applications and case studies concentrate almost exclusively on engineering problems: pendulum balancing, truck backeruppers, cement kilns, antilock braking systems, image pattern recognition, and digital signal processing. Yet the application of fuzzy logic to engineering problems represents only a fraction of its real potential. As a method of encoding and using human knowledge in a form that is very close to the way experts think about difficult, complex problems, fuzzy systems provide the facilities necessary to break through the computational bottlenecks associated with traditional decision support and expert systems. Additionally, fuzzy systems provide a rich and robust method of building systems that include multiple conflicting, cooperating, and collaborating experts (a capability that generally eludes not only symbolic expert system users but analysts who have turned to such related technologies as neural networks and genetic algorithms). Yet the application of fuzzy logic in the areas of decision support, medical systems, database analysis and mining has been largely ignored by both the commercial vendors of decision support products and the knowledge engineers who use them. |
| format | Online |
| id | doab-20.500.12854ir-64764 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | ojs |
| spelling | doab-20.500.12854ir-647642024-04-04T14:41:18Z Fuzzy Systems Taher Azar, Ahmad Mathematical modelling thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics While several books are available today that address the mathematical and philosophical foundations of fuzzy logic, none, unfortunately, provides the practicing knowledge engineer, system analyst, and project manager with specific, practical information about fuzzy system modeling. Those few books that include applications and case studies concentrate almost exclusively on engineering problems: pendulum balancing, truck backeruppers, cement kilns, antilock braking systems, image pattern recognition, and digital signal processing. Yet the application of fuzzy logic to engineering problems represents only a fraction of its real potential. As a method of encoding and using human knowledge in a form that is very close to the way experts think about difficult, complex problems, fuzzy systems provide the facilities necessary to break through the computational bottlenecks associated with traditional decision support and expert systems. Additionally, fuzzy systems provide a rich and robust method of building systems that include multiple conflicting, cooperating, and collaborating experts (a capability that generally eludes not only symbolic expert system users but analysts who have turned to such related technologies as neural networks and genetic algorithms). Yet the application of fuzzy logic in the areas of decision support, medical systems, database analysis and mining has been largely ignored by both the commercial vendors of decision support products and the knowledge engineers who use them. 2021-04-20T14:55:03Z 2021-04-20T14:55:03Z 2010 book ONIX_20210420_9789537619923_120 9789537619923 9789535154884 https://directory.doabooks.org/handle/20.500.12854/64764 eng image/jpeg n/a https://www.intechopen.com/books https://mts.intechopen.com/storage/books/3746/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/133 10.5772/133 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9789537619923 9789535154884 IntechOpen 228 open access |
| spellingShingle | Mathematical modelling thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics Fuzzy Systems |
| title | Fuzzy Systems |
| title_full | Fuzzy Systems |
| title_fullStr | Fuzzy Systems |
| title_full_unstemmed | Fuzzy Systems |
| title_short | Fuzzy Systems |
| title_sort | fuzzy systems |
| topic | Mathematical modelling thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics |
| topic_facet | Mathematical modelling thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics |
| url | ONIX_20210420_9789537619923_120 |