data analysis applications computational (21 Ergebnisse)

Aufl. 2015. 235 mm x 155 mm. XIX, 265 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Adaptation, Learning and Optimization 19.

Paperback. Zustand: Brand New. 138 pages. 8.50x5.51x0.35 inches. In Stock.

Hardcover. Zustand: Used; Very Good. Dispatched, from the UK, within 48 hours of ordering. Though second-hand, the book is still in very good shape. Minimal signs of usage may include very minor creasing on the cover or on the spine.

Zustand: New.

Taschenbuch. Zustand: Neu. Computational Topology for Biomedical Image and Data Analysis | Theory and Applications | Rodrigo Rojas Moraleda (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | CRC Press | EAN 9780367787875 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Seismic Data Analysis by Using Computational Intelligence | Neural Network and Genetic Algorithm Applications for Evaluating Earthquake Key Parameters | Tienfuan Kerh | Taschenbuch | 136 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838383873 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Zustand: New.

Buch. Zustand: Neu. Neuware - 'This book provides an accessible yet rigorous introduction to topology and homology focused on the simplicial space. It presents a compact pipeline from the foundations of topology to biomedical applications'.

Hardcover. Zustand: Brand New. 2015 edition. 288 pages. 9.25x6.25x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

Paperback. Zustand: Brand New. reprint edition. 287 pages. 9.25x6.10x0.68 inches. In Stock.

Hardcover. Zustand: Brand New. 210 pages. 10.32x7.32x0.71 inches. In Stock.

Zustand: New.

Zustand: New. 2022. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 480 pages. 9.49x6.42x1.10 inches. In Stock.

Buch. Zustand: Neu. Neuware - SAR IMAGE ANALYSIS -- A COMPUTATIONAL STATISTICS APPROACHDiscover how to use statistics to extract information from SAR imageryIn SAR Image Analysis -- A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.SAR Image Analysis -- A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.The book also includes:\* Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualization\* Comprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G° distribution, and more general distributions under the multiplicative model\* Practical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distribution\* In-depth examinations of applications, including statistical filters and classificationPerfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis -- A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

Zustand: New. 2020. 3rd Edition. Hardback. . . . . . Books ship from the US and Ireland.

Zustand: New. 2022. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering.This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with related applications.

Taschenbuch. Zustand: Neu. Neuware - Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specifically focusing on sentiment analysis from multifaceted data. The book investigates a wide range of challenges involved in the accurate analysis of online sentiments, including how to i) identify subjective information from text, i.e., exclusion of 'neutral' or 'factual' comments that do not carry sentiment information, ii) identify sentiment polarity, and iii) domain dependency. Spam and fake news detection, short abbreviation, sarcasm, word negation, and a lot of word ambiguity are also explored. Further chapters look at the difficult process of extracting sentiment from different multimodal information (audio, video and text), semantic concepts. In each chapter, the book's authors explore how computational intelligence (CI) techniques, such as deep learning, convolutional neural network, fuzzy and rough set, global optimizers, and hybrid machine learning techniques play an important role in solving the inherent problems of sentiment analysis applications.