S Co 2009 Sixth Conference Complex Data Modeling And Computationally Intensive Statistical Methods For Estimation And Prediction

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Publisher : Maggioli Editore
ISBN 13 : 8838743851
Total Pages : 493 pages
Book Rating : 4.56/5 ( download)

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Download or read book S. Co. 2009. Sixth Conference. Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction written by and published by Maggioli Editore. This book was released on 2009 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Pietro Mantovan
Publisher : Springer Science & Business Media
ISBN 13 : 8847013860
Total Pages : 170 pages
Book Rating : 4.65/5 ( download)

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Download or read book Complex Data Modeling and Computationally Intensive Statistical Methods written by Pietro Mantovan and published by Springer Science & Business Media. This book was released on 2011-01-27 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Selected from the conference "S.Co.2009: Complex Data Modeling and Computationally Intensive Methods for Estimation and Prediction," these 20 papers cover the latest in statistical methods and computational techniques for complex and high dimensional datasets.

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Publisher :
ISBN 13 : 9788847013926
Total Pages : 176 pages
Book Rating : 4.25/5 ( download)

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Download or read book Complex Data Modeling and Computationally Intensive Statistical Methods written by and published by . This book was released on 2011-08-14 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Nikolaos Limnios
Publisher : John Wiley & Sons
ISBN 13 : 1119825032
Total Pages : 336 pages
Book Rating : 4.36/5 ( download)

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Download or read book Statistical Methods and Modeling of Seismogenesis written by Nikolaos Limnios and published by John Wiley & Sons. This book was released on 2021-03-31 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of earthquakes is a multidisciplinary field, an amalgam of geodynamics, mathematics, engineering and more. The overriding commonality between them all is the presence of natural randomness. Stochastic studies (probability, stochastic processes and statistics) can be of different types, for example, the black box approach (one state), the white box approach (multi-state), the simulation of different aspects, and so on. This book has the advantage of bringing together a group of international authors, known for their earthquake-specific approaches, to cover a wide array of these myriad aspects. A variety of topics are presented, including statistical nonparametric and parametric methods, a multi-state system approach, earthquake simulators, post-seismic activity models, time series Markov models with regression, scaling properties and multifractal approaches, selfcorrecting models, the linked stress release model, Markovian arrival models, Poisson-based detection techniques, change point detection techniques on seismicity models, and, finally, semi-Markov models for earthquake forecasting.

Author : Anna Maria Paganoni
Publisher : Springer
ISBN 13 : 9783319385372
Total Pages : 0 pages
Book Rating : 4.72/5 ( download)

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Download or read book Advances in Complex Data Modeling and Computational Methods in Statistics written by Anna Maria Paganoni and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Author : Diego Galar
Publisher : CRC Press
ISBN 13 : 1000518264
Total Pages : 489 pages
Book Rating : 4.69/5 ( download)

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Download or read book Prognostics and Remaining Useful Life (RUL) Estimation written by Diego Galar and published by CRC Press. This book was released on 2021-12-15 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maintenance combines various methods, tools, and techniques in a bid to reduce maintenance costs while increasing the reliability, availability, and security of equipment. Condition-based maintenance (CBM) is one such method, and prognostics forms a key element of a CBM program based on mathematical models for predicting remaining useful life (RUL). Prognostics and Remaining Useful Life (RUL) Estimation: Predicting with Confidence compares the techniques and models used to estimate the RUL of different assets, including a review of the relevant literature on prognostic techniques and their use in the industrial field. This book describes different approaches and prognosis methods for different assets backed up by appropriate case studies. FEATURES Presents a compendium of RUL estimation methods and technologies used in predictive maintenance Describes different approaches and prognosis methods for different assets Includes a comprehensive compilation of methods from model-based and data-driven to hybrid Discusses the benchmarking of RUL estimation methods according to accuracy and uncertainty, depending on the target application, the type of asset, and the forecast performance expected Contains a toolset of methods and a way of deployment aimed at a versatile audience This book is aimed at professionals, senior undergraduates, and graduate students in all interdisciplinary engineering streams that focus on prognosis and maintenance.

Author : Matteo Grigoletto
Publisher : Springer
ISBN 13 : 9788847028708
Total Pages : 228 pages
Book Rating : 4.01/5 ( download)

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Download or read book Complex Models and Computational Methods in Statistics written by Matteo Grigoletto and published by Springer. This book was released on 2013-01-27 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.

Author : Pierre Duchesne
Publisher : Springer Science & Business Media
ISBN 13 : 9780387245546
Total Pages : 354 pages
Book Rating : 4.45/5 ( download)

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Download or read book Statistical Modeling and Analysis for Complex Data Problems written by Pierre Duchesne and published by Springer Science & Business Media. This book was released on 2005-04-12 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: STATISTICAL MODELING AND ANALYSIS FOR COMPLEX DATA PROBLEMS treats some of today’s more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors—largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes—present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets. The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.

Author : Robert Barthorpe
Publisher : Springer
ISBN 13 : 3319747932
Total Pages : 312 pages
Book Rating : 4.34/5 ( download)

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Download or read book Model Validation and Uncertainty Quantification, Volume 3 written by Robert Barthorpe and published by Springer. This book was released on 2018-07-30 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty

Author : Silvelyn Zwanzig
Publisher : CRC Press
ISBN 13 : 9780367194239
Total Pages : 8 pages
Book Rating : 4.36/5 ( download)

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Download or read book Computer Intensive Methods in Statistics written by Silvelyn Zwanzig and published by CRC Press. This book was released on 2019-12-02 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: This class-tested textbook is designed for a semester-long graduate, or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics. It integrates computer science and clinical perspectives. The book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives. Describes various statistical and artificial intelligence techniques including machine learning techniques such as clustering including temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining widely used in health-data analysis. Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange. Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development. Arvind Bansal is a full professor of Computer Science at Kent State University, Kent, Ohio, USA. He received his PhD (1988) from Case Western Reserve University, Cleveland, Ohio, USA. His research publications, and undergraduate and graduate teaching are in artificial intelligence, multimedia systems and languages, bioinformatics, and computational health informatics. Javed Khan is a full professor of Computer Science at Kent State University, Kent, Ohio, USA. He received his PhD (1995) from University of Hawaii at Manoa, USA. His research publications, and undergraduate and graduate teachings are in artificial intelligence, computer networking protocols, educational networks, medical image processing and communication, perceptual enhancement, and automated knowledge acquisition. He has been a long-term Fulbright area expert. S. Kaisar Alam received his PhD (1996) in Electrical Engineering from University of Rochester, Rochester NY, USA. His research publications and teaching are in medical image analysis and genome analysis. He was a member of the research staff in Biomedical Engineering Laboratories during 1998-2013. He has been a Fullbright scholar and a visiting professor at RUTGERS University, NY, USA. Currently, he runs his company for medical image analysis.