Towards Efficient Fuzzy Information Processing: Using the Principle of Information Diffusion
When we learn from books or daily experience, we make associations and draw inferences on the basis of information that is insufficient for under standing. One example of insufficient information may be a small sample derived from observing experiments. With this perspective, the need for de velop...
Gespeichert in:
| Hauptverfasser: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Heidelberg
Physica-Verlag HD
2002
|
| Schriftenreihe: | Studies in Fuzziness and Soft Computing
99 |
| Schlagworte: | |
| Online-Zugang: | FHI01 BTU01 Volltext |
| Zusammenfassung: | When we learn from books or daily experience, we make associations and draw inferences on the basis of information that is insufficient for under standing. One example of insufficient information may be a small sample derived from observing experiments. With this perspective, the need for de veloping a better understanding of the behavior of a small sample presents a problem that is far beyond purely academic importance. During the past 15 years considerable progress has been achieved in the study of this issue in China. One distinguished result is the principle of in formation diffusion. According to this principle, it is possible to partly fill gaps caused by incomplete information by changing crisp observations into fuzzy sets so that one can improve the recognition of relationships between input and output. The principle of information diffusion has been proven suc cessful for the estimation of a probability density function. Many successful applications reflect the advantages of this new approach. It also supports an argument that fuzzy set theory can be used not only in "soft" science where some subjective adjustment is necessary, but also in "hard" science where all data are recorded |
| Beschreibung: | 1 Online-Ressource (XXI, 370 p) |
| ISBN: | 9783790817850 |
| DOI: | 10.1007/978-3-7908-1785-0 |
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| 520 | |a When we learn from books or daily experience, we make associations and draw inferences on the basis of information that is insufficient for under standing. One example of insufficient information may be a small sample derived from observing experiments. With this perspective, the need for de veloping a better understanding of the behavior of a small sample presents a problem that is far beyond purely academic importance. During the past 15 years considerable progress has been achieved in the study of this issue in China. One distinguished result is the principle of in formation diffusion. According to this principle, it is possible to partly fill gaps caused by incomplete information by changing crisp observations into fuzzy sets so that one can improve the recognition of relationships between input and output. The principle of information diffusion has been proven suc cessful for the estimation of a probability density function. Many successful applications reflect the advantages of this new approach. It also supports an argument that fuzzy set theory can be used not only in "soft" science where some subjective adjustment is necessary, but also in "hard" science where all data are recorded | ||
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Datensatz im Suchindex
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| discipline | Mathematik |
| doi_str_mv | 10.1007/978-3-7908-1785-0 |
| format | Electronic eBook |
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| id | DE-604.BV045149537 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:10:04Z |
| institution | BVB |
| isbn | 9783790817850 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030539235 |
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| physical | 1 Online-Ressource (XXI, 370 p) |
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| publisher | Physica-Verlag HD |
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| series2 | Studies in Fuzziness and Soft Computing |
| spelling | Huang, Chongfu Verfasser aut Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion by Chongfu Huang, Yong Shi Heidelberg Physica-Verlag HD 2002 1 Online-Ressource (XXI, 370 p) txt rdacontent c rdamedia cr rdacarrier Studies in Fuzziness and Soft Computing 99 When we learn from books or daily experience, we make associations and draw inferences on the basis of information that is insufficient for under standing. One example of insufficient information may be a small sample derived from observing experiments. With this perspective, the need for de veloping a better understanding of the behavior of a small sample presents a problem that is far beyond purely academic importance. During the past 15 years considerable progress has been achieved in the study of this issue in China. One distinguished result is the principle of in formation diffusion. According to this principle, it is possible to partly fill gaps caused by incomplete information by changing crisp observations into fuzzy sets so that one can improve the recognition of relationships between input and output. The principle of information diffusion has been proven suc cessful for the estimation of a probability density function. Many successful applications reflect the advantages of this new approach. It also supports an argument that fuzzy set theory can be used not only in "soft" science where some subjective adjustment is necessary, but also in "hard" science where all data are recorded Mathematics Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Theory of Computation Computational Intelligence Computers Artificial intelligence Mathematical logic Computational intelligence Shi, Yong aut Erscheint auch als Druck-Ausgabe 9783790825114 https://doi.org/10.1007/978-3-7908-1785-0 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Huang, Chongfu Shi, Yong Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion Mathematics Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Theory of Computation Computational Intelligence Computers Artificial intelligence Mathematical logic Computational intelligence |
| title | Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion |
| title_auth | Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion |
| title_exact_search | Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion |
| title_full | Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion by Chongfu Huang, Yong Shi |
| title_fullStr | Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion by Chongfu Huang, Yong Shi |
| title_full_unstemmed | Towards Efficient Fuzzy Information Processing Using the Principle of Information Diffusion by Chongfu Huang, Yong Shi |
| title_short | Towards Efficient Fuzzy Information Processing |
| title_sort | towards efficient fuzzy information processing using the principle of information diffusion |
| title_sub | Using the Principle of Information Diffusion |
| topic | Mathematics Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Theory of Computation Computational Intelligence Computers Artificial intelligence Mathematical logic Computational intelligence |
| topic_facet | Mathematics Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Theory of Computation Computational Intelligence Computers Artificial intelligence Mathematical logic Computational intelligence |
| url | https://doi.org/10.1007/978-3-7908-1785-0 |
| work_keys_str_mv | AT huangchongfu towardsefficientfuzzyinformationprocessingusingtheprincipleofinformationdiffusion AT shiyong towardsefficientfuzzyinformationprocessingusingtheprincipleofinformationdiffusion |