Advanced Fuzzy Systems Design and Applications:
Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active....
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Heidelberg
Physica-Verlag HD
2003
|
| Schriftenreihe: | Studies in Fuzziness and Soft Computing
112 |
| Schlagworte: | |
| Online-Zugang: | FHI01 BTU01 Volltext |
| Zusammenfassung: | Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted |
| Beschreibung: | 1 Online-Ressource (X, 272 p. 228 illus) |
| ISBN: | 9783790817713 |
| DOI: | 10.1007/978-3-7908-1771-3 |
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| 520 | |a Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted | ||
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Datensatz im Suchindex
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| author | Jin, Yaochu |
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| dewey-ones | 005 - Computer programming, programs, data, security |
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| dewey-search | 005.11 |
| dewey-sort | 15.11 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1007/978-3-7908-1771-3 |
| format | Electronic eBook |
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| id | DE-604.BV045149523 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:10:04Z |
| institution | BVB |
| isbn | 9783790817713 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030539221 |
| oclc_num | 1050952208 |
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| physical | 1 Online-Ressource (X, 272 p. 228 illus) |
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| publishDate | 2003 |
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| publisher | Physica-Verlag HD |
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| series2 | Studies in Fuzziness and Soft Computing |
| spelling | Jin, Yaochu Verfasser aut Advanced Fuzzy Systems Design and Applications by Yaochu Jin Heidelberg Physica-Verlag HD 2003 1 Online-Ressource (X, 272 p. 228 illus) txt rdacontent c rdamedia cr rdacarrier Studies in Fuzziness and Soft Computing 112 Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted Computer Science Programming Techniques Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Data Structures, Cryptology and Information Theory Algorithm Analysis and Problem Complexity Computer science Computer programming Data structures (Computer science) Algorithms Artificial intelligence Mathematical logic Erscheint auch als Druck-Ausgabe 9783790825206 https://doi.org/10.1007/978-3-7908-1771-3 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Jin, Yaochu Advanced Fuzzy Systems Design and Applications Computer Science Programming Techniques Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Data Structures, Cryptology and Information Theory Algorithm Analysis and Problem Complexity Computer science Computer programming Data structures (Computer science) Algorithms Artificial intelligence Mathematical logic |
| title | Advanced Fuzzy Systems Design and Applications |
| title_auth | Advanced Fuzzy Systems Design and Applications |
| title_exact_search | Advanced Fuzzy Systems Design and Applications |
| title_full | Advanced Fuzzy Systems Design and Applications by Yaochu Jin |
| title_fullStr | Advanced Fuzzy Systems Design and Applications by Yaochu Jin |
| title_full_unstemmed | Advanced Fuzzy Systems Design and Applications by Yaochu Jin |
| title_short | Advanced Fuzzy Systems Design and Applications |
| title_sort | advanced fuzzy systems design and applications |
| topic | Computer Science Programming Techniques Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Data Structures, Cryptology and Information Theory Algorithm Analysis and Problem Complexity Computer science Computer programming Data structures (Computer science) Algorithms Artificial intelligence Mathematical logic |
| topic_facet | Computer Science Programming Techniques Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Data Structures, Cryptology and Information Theory Algorithm Analysis and Problem Complexity Computer science Computer programming Data structures (Computer science) Algorithms Artificial intelligence Mathematical logic |
| url | https://doi.org/10.1007/978-3-7908-1771-3 |
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