Data Construction Method Small by Wang Hsiao Fan (7 results)

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  • Language: English

    Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010

    3838398378 / 9783838398372

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    Condition: New. pp. 172.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2012

    3838398378 / 9783838398372

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    Taschenbuch. Condition: Neu. Data Construction Method for Small Sample Sets | Theory and Applications | Hsiao-Fan Wang (u. a.) | Taschenbuch | 172 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783838398372 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

  • Language: English

    Published by LAP LAMBERT Academic Publishing Aug 2010, 2010

    3838398378 / 9783838398372

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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data Construction Method (DCM) based on the multiset division is proposed. The DCM can not only generate addition data within the domain value of the given sample for revealing the data's patterns, but also creates the membership function from the generated data for further applications. In this way, the DCM is taken to filling up the information gaps caused by small-sample-sets. To demonstrate the effectiveness of DCM, after presenting the DCM's theoretic background, properties, and algorithm, we compared the DCM with several existing approaches in estimating the population mean and improving the supervised neural network learning performance. The results show that the DCM performs better in a comparative manner. To show its applicability, we have applied the membership function derived from the DCM data to the studies of predicting the severe earthquakes in Taiwan and forecasting the psychotic episode of individual schizophrenics. The results have shown that the DCM can provide appropriate references for prediction from both spatial and temporal small data sets. 172 pp. Englisch.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2010

    3838398378 / 9783838398372

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    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Wang Hsiao-FanHsiao-Fan Wang is the Distinguished Chair Professor of National Tsing Hua University, Taiwan, ROC. She has been awarded the distinguished researcher of NSC in Taiwan and is the editor of several international journa.

  • Language: English

    Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010

    3838398378 / 9783838398372

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    Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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    Condition: New. Print on Demand pp. 172 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

  • Language: English

    Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010

    3838398378 / 9783838398372

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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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    Condition: New. PRINT ON DEMAND pp. 172.

  • Language: English

    Published by LAP LAMBERT Academic Publishing Aug 2010, 2010

    3838398378 / 9783838398372

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    Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Construction Method (DCM) based on the multiset division is proposed. The DCM can not only generate addition data within the domain value of the given sample for revealing the data's patterns, but also creates the membership function from the generated data for further applications. In this way, the DCM is taken to filling up the information gaps caused by small-sample-sets. To demonstrate the effectiveness of DCM, after presenting the DCM's theoretic background, properties, and algorithm, we compared the DCM with several existing approaches in estimating the population mean and improving the supervised neural network learning performance. The results show that the DCM performs better in a comparative manner. To show its applicability, we have applied the membership function derived from the DCM data to the studies of predicting the severe earthquakes in Taiwan and forecasting the psychotic episode of individual schizophrenics. The results have shown that the DCM can provide appropriate references for prediction from both spatial and temporal small data sets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch.