Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas: In Honor of Hung T. Nguyen`s 75th Birthday, Kreinovich Vladik
Описание: Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques.
Описание: But we know precious little about human reasoning processes, learning mechanisms and the like, and in particular about reasoning with limited, imprecise knowledge. In a sense, intelligent systems are machines which use the most general form of human knowledge together with human reasoning capability to reach decisions.
Описание: But we know precious little about human reasoning processes, learning mechanisms and the like, and in particular about reasoning with limited, imprecise knowledge. In a sense, intelligent systems are machines which use the most general form of human knowledge together with human reasoning capability to reach decisions.
Автор: Hung T. Nguyen; Berlin Wu Название: Fundamentals of Statistics with Fuzzy Data ISBN: 364206857X ISBN-13(EAN): 9783642068577 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Preface.- Real group orbits on flag manifolds.- Complex connections with trivial holonomy.- Indefinite harmonic theory and harmonic spinors.- Twistor theory and the harmonic hull.- Nilpotent Gelfand pairs and spherical transforms of Schwartz functions, II: Taylor expansions on singular sets.- Propagation of the multiplicity-freeness property for holomorphic vector bundles.- Poisson transforms for line bundles from the Shilov boundary to bounded symmetric domains.- Cent(U(n)), cascade of orthogonal roots, and a construction of Lipsman-Wolf.- Weakly harmonic Maa forms and the principal series for SL(2, R).- Holomorphic realization of unitary representations of Banach-Lie groups.- The Segal-Bargmann transform on compact symmetric spaces and their direct limits.- Analysis on flag manifolds and Sobolev inequalities.- Boundary value problems on Riemannian symmetric spaces of noncompact type.- One step spherical functions of the pair (SU(n + 1), U(n)).- Chern-Weil theory for certain infinite-dimensional Lie groups.- On the structure of finite groups with periodic cohomology.
Описание: Chapter 1. My Career and Contributions.- Chapter 2. Understanding the Weber Location Paradigm.- Chapter 3. A general framework for local search applied to the continuous p-median problem.- Chapter 4. Big Triangle Small Triangle Method for the Weber Problem on the Sphere.- Chapter 5. Integer Location Problems.- Chapter 6. Continuous Location Problems.- Chapter 7. Voting for locating facilities: The wisdom of voters.- Chapter 8. Innovations in Statistical Analysis and Genetic Algorithms.- Chapter 9. Hub Location and Related Models.- Chapter 10. Gravity Models in Competitive Facility Location.- Chapter 11. Cover-Based Competitive Location Models.- Chapter 12. The Mean-Value-at-Risk Median Problem on a Network with Random Demand Weights.- Chapter 13. A Bivariate Exponential Distribution.
Описание: Presents research on the incorporation of digital image processing within the IoT field. While highlighting topics such as energy-efficient routing, machine learning, and cryptography, this publication addresses the challenges of transmitting image data and explores further applications of sensor networks.
Описание: Presents research on the incorporation of digital image processing within the IoT field. While highlighting topics such as energy-efficient routing, machine learning, and cryptography, this publication addresses the challenges of transmitting image data and explores further applications of sensor networks.
Описание: Over the past decade, many researchers have proposed applications of fuzzy transform techniques for various image processing topics, such as image coding/decoding, image reduction, image segmentation, image watermarking and image fusion;
Описание: Accordingly, the book offers a valuable guide for researchers and practitioners interested in data processing under uncertainty, and an introduction to the latest trends and techniques in this area, suitable for graduate students.
Автор: Johnson I. Agbinya Название: Applied Data Analytics - Principles and Applications ISBN: 8770220964 ISBN-13(EAN): 9788770220965 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very lage data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications and stock market data, health records and business analytics data are but a few areas of interest. Applications and platforms including R, RapidMiner and Weka provide the basis for analysis, often used by practitioners who pay little to no attention to the underlying mathematics and processes impacting the data. This often leads to an inability to explain results or correct mistakes, or to spot errors.
Applied Data Analytics - Principles and Applications seeks to bridge this missing gap by providing some of the most sought after techniques in big data analytics. Establishing strong foundations in these topics provides practical ease when big data analyses are undertaken using the widely available open source and commercially orientated computation platforms, languages and visualisation systems. The book, when combined with such platforms, provides a complete set of tools required to handle big data and can lead to fast implementations and applications.
The book contains a mixture of machine learning foundations, deep learning, artificial intelligence, statistics and evolutionary learning mathematics written from the usage point of view with rich explanations on what the concepts mean. The author has thus avoided the complexities often associated with these concepts when found in research papers. The tutorial nature of the book and the applications provided are some of the reasons why the book is suitable for undergraduate, postgraduate and big data analytics enthusiasts.
This text should ease the fear of mathematics often associated with practical data analytics and support rapid applications in artificial intelligence, environmental sensor data modelling and analysis, health informatics, business data analytics, data from Internet of Things and deep learning applications.
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