Computational and Statistical Methods for Protein Quantification by Mass Spectrometry, Eidhammer
Автор: Krijnen, Wim P. , Wit, Ernst C. Название: Computational and statistical methods for chemical engineering ISBN: 1032013249 ISBN-13(EAN): 9781032013244 Издательство: Taylor&Francis Рейтинг: Цена: 76550.00 T Наличие на складе: Нет в наличии. Описание: Before the data revolution, most books focused either on mathematical modeling of chemical processes or exploratory chemometrics. This book aims to combine these two approaches and provide aspiring chemical engineers a single, comprehensive account of computational and statistical methods. Each chapter is accompanied by extensive exercises.
Автор: Ponnadurai Ramasami Название: Computational Chemistry Methods: Applications ISBN: 3110629062 ISBN-13(EAN): 9783110629064 Издательство: Walter de Gruyter Цена: 161100.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book reviews a variety of methods in computational chemistry and their applications in different fields of current research. Ab initio methods and regression analyses are discussed with special focus on their application to investigate chemical structures as for example dyes or drug compounds. Further topics are the use of computational methods in the modeling of spectroscopic data or to study reaction mechanisms.
Автор: Shen Liu Название: Computational and Statistical Methods for Analysing Big Data with ISBN: 0128037326 ISBN-13(EAN): 9780128037324 Издательство: Elsevier Science Рейтинг: Цена: 77470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration.
"Computational and Statistical Methods for Analysing Big Data with Applications" starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data.
Advanced computational and statistical methodologies for analysing big data are developed.
Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable.
Case studies are discussed to demonstrate the implementation of the developed methods.
Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation.
Computing code/programs are provided where appropriate.
Автор: Olivier Le Maitre; Omar M Knio Название: Spectral Methods for Uncertainty Quantification ISBN: 9400731922 ISBN-13(EAN): 9789400731929 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents applications of spectral methods to problems of uncertainty propagation and quantification in model-based computations, focusing on the computational and algorithmic features of these methods most useful in dealing with models based on partial differential equations, in particular models arising in simulations of fluid flows.
Автор: Souza De Cursi Eduardo Название: Uncertainty Quantification and Stochastic Modelling with Excel ISBN: 3030777561 ISBN-13(EAN): 9783030777562 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool.
Автор: Chen Название: Stochastic Methods for Modeling and Predicting Complex Dynamical Systems ISBN: 3031222482 ISBN-13(EAN): 9783031222481 Издательство: Springer Рейтинг: Цена: 37260.00 T Наличие на складе: Поставка под заказ. Описание: This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.
Автор: Mcclarren, Ryan G. Название: Uncertainty quantification and predictive computational science ISBN: 3319995243 ISBN-13(EAN): 9783319995243 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties.
Автор: Jadamba Название: Uncertainty Quantification In Varia ISBN: 1138626325 ISBN-13(EAN): 9781138626324 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The primary objective of this book is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields.
Автор: Nishisato Shizuhiko, Beh Eric J., Lombardo Rosaria Название: Modern Quantification Theory: Joint Graphical Display, Biplots, and Alternatives ISBN: 9811624690 ISBN-13(EAN): 9789811624698 Издательство: Springer Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis.
Автор: Raydugin Yuri G. Название: Modern Risk Quantification in Complex Projects: Non-Linear Monte Carlo and System Dynamics Methodologies ISBN: 0198844336 ISBN-13(EAN): 9780198844334 Издательство: Oxford Academ Рейтинг: Цена: 189290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Offers a general participation assessment across five levels of participation and cooperation and the specific behaviours that make up these five levels. The manual details instructions on how to administer the Social Profile, describes how the assessment was developed, and summarized research to support its use. Also included are 14 case studies that illustrate how the Social Profile can be used.
Автор: Luis Chase Название: Uncertainty Quantification: Advances in Research and Applications ISBN: 1536148628 ISBN-13(EAN): 9781536148626 Издательство: Nova Science Рейтинг: Цена: 77080.00 T Наличие на складе: Невозможна поставка. Описание: In recent times, polynomial chaos expansion has emerged as a dominant technique to determine the response uncertainties of a system by propagating the uncertainties of the inputs. In this regard, the opening chapter of Uncertainty Quantification: Advances in Research and Applications, an intrusive approach called Galerkin Projection as well as non-intrusive approaches (such as pseudo-spectral projection and linear regression) are discussed.Next, the authors introduce a new methodology to determine the uncertainties of input parameters using CIRCE software to overcome the reliance on expert judgment. The goal is to determinate and evaluate the uncertainty bounds for physical models related to reflood model of MARS-KS code Vessel module (coupled with COBRA-TF) using both CIRCE and the experimental data of FEBA.Lastly, uncertainties related to rheological model parameters of skeletal muscles are modeled and analyzed, and available data are acquired and fused for hyperelastic constitutive model parameters with Neo-Hookean and Mooney-Rivlin formulations.
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