Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy Etc. Methods and Their Applications, Kosheleva Olga, Shary Sergey P., Xiang Gang
Описание: Introduction.- How to Get More Accurate Estimates.- How to Speed Up Computations.- Towards a Better Understandability of Uncertainty-Estimating Algorithms.- How General Can We Go: What Is Computable and What Is Not.- Decision Making Under Uncertainty.- Conclusions.
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.
How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc.
In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty.
The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.
Автор: Olga Kosheleva; Karen Villaverde Название: How Interval and Fuzzy Techniques Can Improve Teaching ISBN: 3662559919 ISBN-13(EAN): 9783662559918 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction: Need for Interval and Fuzzy Techniques in Math and Science Education.-Part I How to Motivate Students.-How to Motivate Students? .-Need to Understand the Presence of Uncertainty: Emphasizing Paradoxes as a (Seemingly Paradoxical) Way to Enhance the Learning of (Strict) Mathematics .-Uncertainty-Related Example Explaining Why Geometry Is Useful: Geometry of a Plane .-Uncertainty-Related Example Explaining Why Calculus Is Useful: Example of the Mean Value Theorem .-How to Enhance Student Motivations by Borrowing from Ancient Tradition: Egyptian Fractions .-How to Enhance Student Motivations by Borrowing from Ancient Tradition: Mayan and Babylonian Arithmetics .-How to Enhance Student Motivations by Borrowing from Ancient Tradition: Babylonian Method of Computing the Square Root .-How to Enhance Student Motivations by Borrowing from Ancient Tradition: Russian Peasant Multiplication Algorithm .-How to Enhance Student Motivations by Borrowing from Modern Practices: Geometric Approach to Error-Less Counting .-How to Enhance Student Motivations by Borrowing from Modern Practices: Can We Learn Algorithms from People Who Compute Fast.-How to Enhance a General Student Motivation to Study: Asymmetric Paternalism .-Financial Motivation: How to Incentivize Students to Graduate Faster.-Part II In What Order to Present the Material.-In What Order to Present the Material.-Spiral Curriculum: Towards Mathematical Foundations.-How Much Time to Allocate to Each Topic?.-What is Wrong with Teaching to the Test: Uncertainty Techniques Help in Understanding the Controversy.-In What Order to Present the Material: Fractal Approach.-How AI-Type Uncertainty Ideas Can Improve Inter-Disciplinary Education and Collaboration: Lessons from a Case Study.-In What Order to Present the Material Within Each Topic: Concrete-First vs. Abstract-First .-Part III How to Select an Appropriate Way of Teaching Each Topic.-How to Select an Appropriate Way of Teaching Each Topic .-What is the Best Way to Distribute the Teacher's Efforts Among Students .-What is the Best Way to Allocate Teacher's Efforts: How Accurately Should We Write on the Board? When Marking Comments on Student Papers? .-How to Divide Students into Groups so as to Optimize Learning .-How to Divide Students into Groups: Importance of Diversity and Need for Intelligent Techniques to Further Enhance the Advantage of Groups with Diversity in Problem Solving .-A Minor but Important Aspect of Teaching Large Classes: When to Let in Late Students? .-Part IV How to Assess Students, Teachers, and Teaching Techniques.-How to Assess Students, Teachers, and Teaching Techniques.-How to Assess Students: Rewarding Results or Rewarding Efforts?.-How to Assess Students: Assess Frequently.-How to Assess Students: Surprise Them.-How to Assess Individual Contributions to a Group Project.-How to Access Students's Readiness for the Next Class.-How to Assess Students: Beyond Weighted Average.-How to Assess a Class .-How to Assess Teachers.-How to Assess Teaching Teachniques.-How to Assess Universities: Defining Average Class Size in a Way Which Is Most Adequate for Teaching Effectiveness.-Conclusions .
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: On various examples ranging from geosciences to environmental sciences, thisbook explains how to generate an adequate description of uncertainty, how to justifysemiheuristic algorithms for processing uncertainty, and how to make these algorithmsmore computationally efficient.
Автор: Olga Kosheleva; Karen Villaverde Название: How Interval and Fuzzy Techniques Can Improve Teaching ISBN: 3662572567 ISBN-13(EAN): 9783662572566 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains how to teach better and presents the latest research on processing educational data and presents traditional statistical techniques as well as probabilistic, interval, and fuzzy approaches. Teaching is a very rewarding activity; it is also a very difficult one – because it is largely an art. There is a lot of advice on teaching available, but it is usually informal and is not easy to follow. To remedy this situation, it is reasonable to use techniques specifically designed to handle such imprecise knowledge: the fuzzy logic techniques. Since there are a large number of statistical studies of different teaching techniques, the authors combined statistical and fuzzy approaches to process the educational data in order to provide insights into improving all the stages of the education process: from forming a curriculum to deciding in which order to present the material to grading the assignments and exams. The authors do not claim to have solved all the problems of education. Instead they show, using numerous examples, that an innovative combination of different uncertainty techniques can improve teaching. The book offers teachers and instructors valuable advice and provides researchers in pedagogical and fuzzy areas with techniques to further advance teaching.
Описание: This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations.
Автор: P?kala Название: Uncertainty Data in Interval-Valued Fuzzy Set Theory ISBN: 3319939092 ISBN-13(EAN): 9783319939094 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov`s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information.
Автор: Barbara P?kala Название: Uncertainty Data in Interval-Valued Fuzzy Set Theory ISBN: 3030067432 ISBN-13(EAN): 9783030067434 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Поставка под заказ.
Описание: This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.
Описание: It also examines approximations of four notable probability distributions (Weibull, exponential, logistic and normal) using a unified probability distribution function, and presents a fuzzy arithmetic-based time series model that provides an easy-to-use forecasting technique.
Автор: Vladik Kreinovich; Nguyen Ngoc Thach; Nguyen Duc T Название: Beyond Traditional Probabilistic Methods in Economics ISBN: 3030041999 ISBN-13(EAN): 9783030041991 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Поставка под заказ.
Описание: This book presents recent research on probabilistic methods in economics, from machine learning to statistical analysis. Economics is a very important – and at the same a very difficult discipline. It is not easy to predict how an economy will evolve or to identify the measures needed to make an economy prosper. One of the main reasons for this is the high level of uncertainty: different difficult-to-predict events can influence the future economic behavior. To make good predictions and reasonable recommendations, this uncertainty has to be taken into account.In the past, most related research results were based on using traditional techniques from probability and statistics, such as p-value-based hypothesis testing. These techniques led to numerous successful applications, but in the last decades, several examples have emerged showing that these techniques often lead to unreliable and inaccurate predictions. It is therefore necessary to come up with new techniques for processing the corresponding uncertainty that go beyond the traditional probabilistic techniques.This book focuses on such techniques, their economic applications and the remaining challenges, presenting both related theoretical developments and their practical applications.
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