Найти книгу: "Statistical Methods for Fuzzy Data"

Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.

Content

Introduction

Upholstery tools and materials

Manual dismantling of interior parts

Mastering the art of sewing

Making upholstery pattern

Examples of ready patterns

Covers

Installation instructions autocovers

Leather interior with their own hands

Padding of the saloon ceiling

We produce door skin

Padding vinyl interior

Padding upholstery motorcycle seats

Renovation of the old sagging armchair

Eliminating failures heated seat

Nano Textile upholstery

Technology smart car flocking

The interiors of the converted cars

В книге рассматриваются основы нечеткого моделирования – нового направления применения наукоемких технологий для решения практических задач. Подробно описываются базовые понятия теории нечетких множеств и нечеткой логики, необходимые для построения нечетких моделей систем в бизнесе, технике и политике. Рассматриваются особенности нечеткого моделирования в средах MATLAB и fuzzyTECH. Изложение сопровождается примерами разработки отдельных нечетких моделей и иллюстрациями выполнения всех необходимых операций с нечеткими множествами. Для системных аналитиков, программистов и студентов вузов.

Based on a set of four research parameters, this book discusses the development of research questions and hypotheses, naturalistic and experimental research, data collection, and validation of research instruments. Each chapter includes examples and activities.