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: 24165.00 р. 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.
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.
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: Olivier Le Maitre; Omar M Knio Название: Spectral Methods for Uncertainty Quantification ISBN: 9400731922 ISBN-13(EAN): 9789400731929 Издательство: Springer Рейтинг: Цена: 10366.00 р. 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.
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.
Описание: An Accelerated Course with Applications in Computational Sciences and Engineering
Автор: Jadamba Название: Uncertainty Quantification In Varia ISBN: 1138626325 ISBN-13(EAN): 9781138626324 Издательство: Taylor&Francis Рейтинг: Цена: 18374.00 р. 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.
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.
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: Nishisato Shizuhiko Название: Optimal Quantification and Symmetry ISBN: 981169169X ISBN-13(EAN): 9789811691690 Издательство: Springer Рейтинг: Цена: 15855.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a unique new look at the familiar quantification theory from the point of view of mathematical symmetry and spatial symmetry.
Автор: Zoltan Kovacs Название: Probabilistic Safety Assessment of WWER440 Reactors ISBN: 3319085476 ISBN-13(EAN): 9783319085470 Издательство: Springer Рейтинг: Цена: 15957.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- The nuclear power plant with WWER440 reactors.- Level 1 full power PSA.- Level 1 low power and shutdown PSA.- Level 2 PSA.- PSA applications.- Conclusions.
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