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Towards Efficient Fuzzy Information Processing: Using the Principle of Information Diffusion (Studies in Fuzziness and Soft Computing) - Softcover
Synopsis
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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- PublisherPhysica
- Publication date2010
- ISBN 10 3790825115
- ISBN 13 9783790825114
- BindingPaperback
- Number of pages391
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Towards Efficient Fuzzy Information Processing: Using The Principle Of Information Diffusion (Studies In Fuzziness And Soft Computing) by Huang, Chongfu [Paperback ]
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Physica-Verlag HD Okt 2010, 2010
ISBN 10: 3790825115
ISBN 13: 9783790825114
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 396 pp. Englisch. Seller Inventory # 9783790825114
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783790825114
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