Author: Daniela Steffes-lai
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832536965
Category : Mathematics
Languages : en
Pages : 232
Book Description
This work addresses the analysis of a sequential chain of processing steps, which is particularly important for the manufacture of robust product components. In each processing step, the material properties may have changed and distributions of related characteristics, for example, strains, may become inhomogeneous. For this reason, the history of the process including design-parameter uncertainties becomes relevant for subsequent processing steps. Therefore, we have developed a methodology, called PRO-CHAIN, which enables an efficient analysis, quantification, and propagation of uncertainties for complex process chains locally on the entire mesh. This innovative methodology has the objective to improve the overall forecast quality, specifically, in local regions of interest, while minimizing the computational effort of subsequent analysis steps. We have demonstrated the benefits and efficiency of the methodology proposed by means of real applications from the automotive industry.
Approximation Methods for High Dimensional Simulation Results - Parameter Sensitivity Analysis and Propagation of Variations for Process Chains
Author: Daniela Steffes-lai
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832536965
Category : Mathematics
Languages : en
Pages : 232
Book Description
This work addresses the analysis of a sequential chain of processing steps, which is particularly important for the manufacture of robust product components. In each processing step, the material properties may have changed and distributions of related characteristics, for example, strains, may become inhomogeneous. For this reason, the history of the process including design-parameter uncertainties becomes relevant for subsequent processing steps. Therefore, we have developed a methodology, called PRO-CHAIN, which enables an efficient analysis, quantification, and propagation of uncertainties for complex process chains locally on the entire mesh. This innovative methodology has the objective to improve the overall forecast quality, specifically, in local regions of interest, while minimizing the computational effort of subsequent analysis steps. We have demonstrated the benefits and efficiency of the methodology proposed by means of real applications from the automotive industry.
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832536965
Category : Mathematics
Languages : en
Pages : 232
Book Description
This work addresses the analysis of a sequential chain of processing steps, which is particularly important for the manufacture of robust product components. In each processing step, the material properties may have changed and distributions of related characteristics, for example, strains, may become inhomogeneous. For this reason, the history of the process including design-parameter uncertainties becomes relevant for subsequent processing steps. Therefore, we have developed a methodology, called PRO-CHAIN, which enables an efficient analysis, quantification, and propagation of uncertainties for complex process chains locally on the entire mesh. This innovative methodology has the objective to improve the overall forecast quality, specifically, in local regions of interest, while minimizing the computational effort of subsequent analysis steps. We have demonstrated the benefits and efficiency of the methodology proposed by means of real applications from the automotive industry.
Sparse Polynomial Approximation of High-Dimensional Functions
Author: Ben Adcock
Publisher: Society for Industrial and Applied Mathematics (SIAM)
ISBN: 9781611976878
Category : Approximation theory
Languages : en
Pages : 0
Book Description
"This is a book about polynomial approximation in high dimensions"--
Publisher: Society for Industrial and Applied Mathematics (SIAM)
ISBN: 9781611976878
Category : Approximation theory
Languages : en
Pages : 0
Book Description
"This is a book about polynomial approximation in high dimensions"--
High-Dimensional Probability
Author: Roman Vershynin
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299
Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299
Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
High-Dimensional Statistics
Author: Martin J. Wainwright
Publisher: Cambridge University Press
ISBN: 1108498027
Category : Business & Economics
Languages : en
Pages : 571
Book Description
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
Publisher: Cambridge University Press
ISBN: 1108498027
Category : Business & Economics
Languages : en
Pages : 571
Book Description
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
Sustainability of the Theories Developed by Mathematical Finance and Mathematical Economics with Applications
Author: Wing-Keung Wong
Publisher: MDPI
ISBN: 3039365312
Category : Business & Economics
Languages : en
Pages : 382
Book Description
The topics studied in this Special Issue include a wide range of areas in finance, economics, tourism, management, marketing, and education. The topics in finance include stock market, volatility and excess returns, REIT, warrant and options, herding behavior and trading strategy, supply finance, and corporate finance. The topics in economics including economic growth, income poverty, and political economics.
Publisher: MDPI
ISBN: 3039365312
Category : Business & Economics
Languages : en
Pages : 382
Book Description
The topics studied in this Special Issue include a wide range of areas in finance, economics, tourism, management, marketing, and education. The topics in finance include stock market, volatility and excess returns, REIT, warrant and options, herding behavior and trading strategy, supply finance, and corporate finance. The topics in economics including economic growth, income poverty, and political economics.
MultiMedia Modeling
Author: Qi Tian
Publisher: Springer
ISBN: 3319276743
Category : Computers
Languages : en
Pages : 450
Book Description
The two-volume set LNCS 9516 and 9517 constitutes the thoroughly refereed proceedings of the 22nd International Conference on Multimedia Modeling, MMM 2016, held in Miami, FL, USA, in January 2016. The 32 revised full papers and 52 poster papers were carefully reviewed and selected from 117 submissions. In addition 20 papers were accepted for five special sessions out of 38 submissions as well as 7 demonstrations (from 11 submissions) and 9 video showcase papers. The papers are organized in topical sections on video content analysis, social media analysis, object recognition and system, multimedia retrieval and ranking, multimedia representation, machine learning in multimedia, and interaction and mobile. The special sessions are: good practices in multimedia modeling; semantics discovery from multimedia big data; perception, aesthetics, and emotion in multimedia quality modeling; multimodal learning and computing for human activity understanding; and perspectives on multimedia analytics./div
Publisher: Springer
ISBN: 3319276743
Category : Computers
Languages : en
Pages : 450
Book Description
The two-volume set LNCS 9516 and 9517 constitutes the thoroughly refereed proceedings of the 22nd International Conference on Multimedia Modeling, MMM 2016, held in Miami, FL, USA, in January 2016. The 32 revised full papers and 52 poster papers were carefully reviewed and selected from 117 submissions. In addition 20 papers were accepted for five special sessions out of 38 submissions as well as 7 demonstrations (from 11 submissions) and 9 video showcase papers. The papers are organized in topical sections on video content analysis, social media analysis, object recognition and system, multimedia retrieval and ranking, multimedia representation, machine learning in multimedia, and interaction and mobile. The special sessions are: good practices in multimedia modeling; semantics discovery from multimedia big data; perception, aesthetics, and emotion in multimedia quality modeling; multimodal learning and computing for human activity understanding; and perspectives on multimedia analytics./div
Monte Carlo Methods in Finance
Author: William Johnson
Publisher: HiTeX Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 454
Book Description
"Monte Carlo Methods in Finance: Simulation Techniques for Market Modeling" presents a sophisticated and in-depth exploration of Monte Carlo simulations, a vital tool in modern financial analysis. This book deftly bridges the gap between theoretical constructs and practical implementation, guiding readers through a comprehensive understanding of how these methods unlock insights into the complexities of financial markets. Through capturing the randomness and volatility inherent in financial systems, Monte Carlo techniques provide a structured approach to modeling uncertainty, pricing derivatives, optimizing portfolios, and managing risk with precision and rigor. With a focus on making advanced concepts accessible, this book seamlessly integrates foundational theories with real-world applications. Each chapter meticulously explores critical subjects—ranging from stochastic processes and option pricing to credit risk and machine learning—while providing clear step-by-step Python implementations. As readers progress, they gain robust skills in executing simulations and interpreting results, empowering them to make informed financial decisions. Whether you are a student, a practitioner, or someone with a keen interest in quantitative finance, this text serves as an invaluable resource for mastering the intricacies of Monte Carlo methods and their impactful role in shaping contemporary finance.
Publisher: HiTeX Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 454
Book Description
"Monte Carlo Methods in Finance: Simulation Techniques for Market Modeling" presents a sophisticated and in-depth exploration of Monte Carlo simulations, a vital tool in modern financial analysis. This book deftly bridges the gap between theoretical constructs and practical implementation, guiding readers through a comprehensive understanding of how these methods unlock insights into the complexities of financial markets. Through capturing the randomness and volatility inherent in financial systems, Monte Carlo techniques provide a structured approach to modeling uncertainty, pricing derivatives, optimizing portfolios, and managing risk with precision and rigor. With a focus on making advanced concepts accessible, this book seamlessly integrates foundational theories with real-world applications. Each chapter meticulously explores critical subjects—ranging from stochastic processes and option pricing to credit risk and machine learning—while providing clear step-by-step Python implementations. As readers progress, they gain robust skills in executing simulations and interpreting results, empowering them to make informed financial decisions. Whether you are a student, a practitioner, or someone with a keen interest in quantitative finance, this text serves as an invaluable resource for mastering the intricacies of Monte Carlo methods and their impactful role in shaping contemporary finance.
Proceedings of the Third International Conference on Contemporary Issues in Computer and Information Sciences (CICIS 2012)
Author:
Publisher: Universal-Publishers
ISBN: 161233623X
Category :
Languages : en
Pages : 625
Book Description
Publisher: Universal-Publishers
ISBN: 161233623X
Category :
Languages : en
Pages : 625
Book Description
Computational Methods of Feature Selection
Author: Huan Liu
Publisher: CRC Press
ISBN: 1584888792
Category : Business & Economics
Languages : en
Pages : 437
Book Description
Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Publisher: CRC Press
ISBN: 1584888792
Category : Business & Economics
Languages : en
Pages : 437
Book Description
Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Compression of an array of similar crash test simulation results
Author: Stefan Peter Müller
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832554440
Category : Mathematics
Languages : en
Pages : 232
Book Description
Big data thrives on extracting knowledge from a large number of data sets. But how is an application possible when a single data set is several gigabytes in size? The innovative data compression techniques from the field of machine learning and modeling using Bayesian networks, which have been theoretically developed and practically implemented here, can reduce these huge amounts of data to a manageable size. By eliminating redundancies in location, time, and between simulation results, data reductions to less than 1% of the original size are possible. The developed method represents a promising approach whose use goes far beyond the application example of crash test simulations chosen here.
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832554440
Category : Mathematics
Languages : en
Pages : 232
Book Description
Big data thrives on extracting knowledge from a large number of data sets. But how is an application possible when a single data set is several gigabytes in size? The innovative data compression techniques from the field of machine learning and modeling using Bayesian networks, which have been theoretically developed and practically implemented here, can reduce these huge amounts of data to a manageable size. By eliminating redundancies in location, time, and between simulation results, data reductions to less than 1% of the original size are possible. The developed method represents a promising approach whose use goes far beyond the application example of crash test simulations chosen here.