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 inf… More...
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.; PDF; Scientific, Technical and Medical > Mathematical foundations, Physica-Verlag HD<
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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 i… More...
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. Books > Mathematics eBook, Springer Shop<
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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 in… More...
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. Books > Mathematics eBook, Springer Shop<
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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 in… More...
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., Physica<
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Towards Efficient Fuzzy Information Processing ab 138.99 € als pdf eBook: Using the Principle of Information Diffusion. Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Technik, Medien > B… More...
Towards Efficient Fuzzy Information Processing ab 138.99 € als pdf eBook: Using the Principle of Information Diffusion. Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Technik, Medien > Bücher, Towards Efficient Fuzzy Information Processing - eBook als pdf von Chongfu Huang/ Yong Shi - Physica-Verlag HD - 9783790817850<
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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 inf… More...
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.; PDF; Scientific, Technical and Medical > Mathematical foundations, Physica-Verlag HD<
No. 9783790817850. Shipping costs:Instock, Despatched same working day before 3pm, zzgl. Versandkosten., plus shipping costs
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 i… More...
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. Books > Mathematics eBook, Springer Shop<
new in stock. Shipping costs:zzgl. Versandkosten. (EUR 0.00)
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 in… More...
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. Books > Mathematics eBook, Springer Shop<
new in stock. Shipping costs:zzgl. Versandkosten. (EUR 0.00)
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 in… More...
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., Physica<
Nr. 978-3-7908-1785-0. Shipping costs:Worldwide free shipping, , DE. (EUR 0.00)
Towards Efficient Fuzzy Information Processing ab 138.99 € als pdf eBook: Using the Principle of Information Diffusion. Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Technik, Medien > B… More...
Towards Efficient Fuzzy Information Processing ab 138.99 € als pdf eBook: Using the Principle of Information Diffusion. Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Technik, Medien > Bücher, Towards Efficient Fuzzy Information Processing - eBook als pdf von Chongfu Huang/ Yong Shi - Physica-Verlag HD - 9783790817850<
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Details of the book - Towards Efficient Fuzzy Information Processing
EAN (ISBN-13): 9783790817850 Publishing year: 2012 Publisher: Physica-Verlag HD
Book in our database since 2017-05-08T06:01:08+01:00 (London) Detail page last modified on 2024-03-13T09:41:40+00:00 (London) ISBN/EAN: 9783790817850
ISBN - alternate spelling: 978-3-7908-1785-0 Alternate spelling and related search-keywords: Book author: trzaskalik Book title: information
Information from Publisher
Author: Chongfu Huang; Yong Shi Title: Studies in Fuzziness and Soft Computing; Towards Efficient Fuzzy Information Processing - Using the Principle of Information Diffusion Publisher: Physica; Physica 370 Pages Publishing year: 2012-11-03 Heidelberg; DE Language: English 96,29 € (DE) 99,00 € (AT) 118,00 CHF (CH) Available XXI, 370 p.
I: Principle of Information Diffusion.- 1. Introduction.- 2. Information Matrix.- 3. Some Concepts From Probability and Statistics.- 4. Information Distribution.- 5. Information Diffusion.- 6. Quadratic Diffusion.- 7. Normal Diffusion.- II: Applications.- 8. Estimation of Epicentral Intensity.- 9. Estimation of Isoseismal Area.- 10. Fuzzy Risk Analysis.- 11. System Analytic Model for Natural Disasters.- 12. Fuzzy Risk Calculation.- List of Special Symbols. Book on fuzzy concepts to explain the dynamics and limitation of kernel functions Gives diffusion models for practical problems Includes supplementary material: sn.pub/extras
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