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Condition: As New. Unread book in perfect condition.
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Spatial Autoregression Sar Model : Parameter Estimation Techniques
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 84.
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Spatial Autoregression Sar Model : Parameter Estimation Techniques
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Spatial Autoregression (Sar) Model: Parameter Estimation Techniques
Language: English
Published by Springer-Verlag New York Inc, 2012
ISBN 10: 1461418410 ISBN 13: 9781461418412
Paperback. Condition: Brand New. 73 pages. 9.00x6.00x0.25 inches. In Stock.
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Spatial AutoRegression (SAR) Model : Parameter Estimation Techniques
Language: English
Published by Springer New York, Springer US, 2012
ISBN 10: 1461418410 ISBN 13: 9781461418412
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This book explores computational structure of the exact and approximate spatialautoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function.The second part of the book introduces theory on SAR model solutions. The third part of the book applies parallel processing techniques to the exact SAR model solutions. Parallel formulations of the SAR model parameter estimation procedure based on ML theory are probed using data parallelism with load-balancing techniques.Although this parallel implementation showed scalability up to eight processors, the exact SAR model solution still suffers from high computational complexity and memory requirements. These limitations have led the book to investigate serial and parallel approximate solutions for SAR model parameter estimation. In the fourth and fifth parts of the book, two candidate approximate-semi-sparse solutions of the SAR model based on Taylor's Series expansion and Chebyshev Polynomials are presented. Experiments show that the differences between exact and approximate SAR parameter estimates have no significant effect on the prediction accuracy.In the last part of the book, we developed a new ML based approximate SAR model solution and its variants in the next part of the thesis. The new approximate SAR model solution is called the Gauss-Lanczos approximated SAR model solution. We algebraically rank the error of the Chebyshev Polynomial approximation, Taylor's Series approximation and the Gauss-Lanczos approximation to the solution of the SAR model and its variants. In other words, we established a novel relationship between the error in the log-det term, which is the approximated term in the concentrated log-likelihood function and the error in estimating the SAR parameter for all of the approximate SAR model solutions.
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Fine-Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment: Approaches, Case Studies and Python Applications (Studies in Fuzziness and Soft Computing, 398)
Book 164 of 183: Studies in Fuzziness and Soft ComputingSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Türk mimarisinin gelisimi ve Mimar Sinan.
Published by Türkiye Is Bankasi Kültür Yayinlari, Istanbul, 1975
Seller: Khalkedon Rare Books ABA, ILAB, IOBA, ESA, Istanbul, Turkey
Association Member: ABA ESA ILAB IOBA
Seller rating 5 out of 5 stars
Dust jacket. Condition: Very Good. Dust Jacket Condition: Very Good. Original bdg. with original dust wrapper. There's tear the edges of DJ. [xi], 397 p. In Turkish. Color and b/w ills. Türk mimarisinin gelisimi ve Mimar Sinan. TURKISH AND ISLAMIC ARTS Ottoman architecture Architect Sinan History of art.
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Fine-Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment .
Book 164 of 183: Studies in Fuzziness and Soft ComputingLanguage: English
Published by Springer International Publishing, 2020
ISBN 10: 3030521478 ISBN 13: 9783030521479
Gebunden. Condition: New.
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This book explores computational structure of the exact and approximate spatial autoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function. The second part of the book introduces theory on SAR model solutions. The third part of the book applies parallel processing techniques to the exact SAR model solutions. Parallel formulations of the SAR model parameter estimation procedure based on ML theory are probed using data parallelism with load-balancing techniques. Although this parallel implementation showed scalability up to eight processors, the exact SAR model solution still suffers from high computational complexity and memory requirements. These limitations have led the book to investigate serial and parallel approximate solutions for SAR model parameter estimation. In the fourth and fifth parts of the book, two candidate approximate-semi-sparse solutions of the SAR model based on Taylor's Series expansion and Chebyshev Polynomials are presented. Experiments show that the differences between exact and approximate SAR parameter estimates have no significant effect on the prediction accuracy. In the last part of the book, we developed a new ML based approximate SAR model solution and its variants in the next part of the thesis. The new approximate SAR model solution is called the Gauss-Lanczos approximated SAR model solution. We algebraically rank the error of the Chebyshev Polynomial approximation, Taylor's Series approximation and the Gauss-Lanczos approximation to the solution of the SAR model and its variants. In other words, we established a novel relationship between the error in the log-det term, which is the approximated term in the concentrated log-likelihood function and the error in estimating the SAR parameter for all of the approximate SAR model solutions.
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Hardcover. Condition: Brand New. 178 pages. 9.25x6.10x9.21 inches. In Stock.
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Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Language: English
Published by Medical Info Science Reference, 2020
ISBN 10: 1799825817 ISBN 13: 9781799825814
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Language: English
Published by Medical Info Science Reference, 2020
ISBN 10: 1799825817 ISBN 13: 9781799825814
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Language: English
Published by Medical Info Science Reference, 2020
ISBN 10: 1799825817 ISBN 13: 9781799825814
Condition: New.
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Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Language: English
Published by Medical Info Science Reference, 2020
ISBN 10: 1799825817 ISBN 13: 9781799825814
Condition: As New. Unread book in perfect condition.
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Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Language: English
Published by Medical Info Science Reference, 2020
ISBN 10: 1799825817 ISBN 13: 9781799825814
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 299.21
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Language: English
Published by Medical Info Science Reference, 2020
ISBN 10: 1799825817 ISBN 13: 9781799825814
hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Spatial AutoRegression (SAR) Model
Language: English
Published by Springer New York, Springer Mär 2012, 2012
ISBN 10: 1461418410 ISBN 13: 9781461418412
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This book explores computational structure of the exact and approximate spatialautoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function.The second part of the book introduces theory on SAR model solutions. The third part of the book applies parallel processing techniques to the exact SAR model solutions. Parallel formulations of the SAR model parameter estimation procedure based on ML theory are probed using data parallelism with load-balancing techniques.Although this parallel implementation showed scalability up to eight processors, the exact SAR model solution still suffers from high computational complexity and memory requirements. These limitations have led the book to investigate serial and parallel approximate solutions for SAR model parameter estimation. In the fourth and fifth parts of the book, two candidate approximate-semi-sparse solutions of the SAR model based on Taylor's Series expansion and Chebyshev Polynomials are presented. Experiments show that the differences between exact and approximate SAR parameter estimates have no significant effect on the prediction accuracy.In the last part of the book, we developed a new ML based approximate SAR model solution and its variants in the next part of the thesis. The new approximate SAR model solution is called the Gauss-Lanczos approximated SAR model solution. We algebraically rank the error of the Chebyshev Polynomial approximation, Taylor's Series approximation and the Gauss-Lanczos approximation to the solution of the SAR model and its variants. In other words, we established a novel relationship between the error in the log-det term, which is the approximated term in the concentrated log-likelihood function and the error in estimating the SAR parameter for all of the approximate SAR model solutions. 84 pp. Englisch.
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Condition: New. Print on Demand pp. 84 26 Illus.
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Condition: New. PRINT ON DEMAND pp. 84.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This book explores computational structure of the exact and ap.
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Fine-Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment
Book 164 of 183: Studies in Fuzziness and Soft ComputingLanguage: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030521508 ISBN 13: 9783030521509
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents a number of approaches to Fine-Kinney-based multi-criteria occupational risk-assessment. For each proposed approach, it provides case studies demonstrating their applicability, as well as Python coding, which will enable readers to imp.
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