Название: Потоки в сетях: учебное пособие
Автор: Еремеева Л.Э.
Издательство: Сыктывкар: Сыктывкарский лесной институт
Год: 2012
Страниц: 100
Формат: djvu
Размер: 12,4 Мб
Язык: Русский

После изучения дисциплины «Потоки в сетях» студент должен знать: взаимосвязь между различными потоковыми задачами и методы их решения; способы представления, хранения и преобразования данных; основные понятия, используемые в сетевом моделировании; способы сведения прикладных задач к потоковым задачам; основные алгоритмы потокового программирования; технологию решения оптимизационных потоковых задач на ЭВМ.

Название: A Modern Introduction to Mathematical Analysis
Автор: Alessandro Fonda
Издательство: Birkhauser/Springer
Год: 2023
Страниц: 442
Язык: английский
Формат: pdf (true), epub
Размер: 27.7 MB

This textbook presents all the basics for the first two years of a course in mathematical analysis, from the natural numbers to Stokes-Cartan Theorem. The main novelty which distinguishes this book is the choice of introducing the Kurzweil-Henstock integral from the very beginning. Although this approach requires a small additional effort by the student, it will be compensated by a substantial advantage in the development of the theory, and later on when learning about more advanced topics. The text guides the reader with clarity in the discovery of the many different subjects, providing all necessary tools – no preliminaries are needed. Both students and their instructors will benefit from this book and its novel approach, turning their course in mathematical analysis into a gratifying and successful experience.

Название: Высшая математика. Практикум для студентов технических и экономических специальностей
Автор: Горелов Г. Н., Горлач Б. А., Додонова Н. Л., Ефимов Е. А., Подклетнова С. В., Ростова Е. П.
Издательство: СПб.: Лань
Год: 2020
Cтраниц: 676
Формат: pdf (ocr)
Размер: 11 мб
Язык: русский

Содержание соответствует программам математической подготовки бакалавров и специалистов технических и экономических направлений. Приводятся примеры приложения математики к решению конкретных технических и экономических задач. Разобраны решения типовых задач. Даны условия задач для самостоятельного решения и задания для выполнения расчетных работ. Приведены вопросы для самопроверки усвоения материала и типовые контрольные работы.

Название: Bayesian Real-Time System Identification: From Centralized to Distributed Approach
Автор: Ke Huang, Ka-Veng Yuen
Издательство: Springer
Год: 2023
Страниц: 286
Язык: английский
Формат: pdf (true)
Размер: 13.5 MB

System identification aims at estimating the physical parameters associated with a mathematical model from measured data. It is applicable to virtually all areas of science and engineering. Any discipline concerned with mathematical modeling of its underlying system is a likely candidate for system identification. This includes statistical physics, information sciences, chemical engineering, electrical engineering, etc. Real-time system identification provides comprehensive treatment for the challenging issue in dynamical systems: tracking time-varying systems. It is desirable for promptly acquiring information from the system for monitoring and control purposes. This book aims to provide novel identification insights for dealing with some challenging identification problems for time-varying dynamical systems. It offers two different perspectives to data processing for system identification, namely, centralized and distributed, compared with conventional centralized approaches. Centralized identification requires transmitting all measured data to a single processing unit. A number of methods for parameter estimation have been developed in this scope under different working conditions. Real-time model class selection is also considered and it is incorporated with parameter estimation for system identification purposes.

Название: Математика в задачах с решениями: учебное пособие для СПО, 9-е изд.
Автор: Лисичкин В.Т., Соловейчик И.Л.
Издательство: Лань
Год: 2022
Страниц: 465
Язык: русский
Формат: pdf
Размер: 15,3 MB

Настоящее пособие предназначено для учащихся техникумов и может быть с успехом использовано учащимиси 10-11-х классов средней школы. Оно начинается с вводной главы, в которую включено несколько тем для повторения школьного курса математики. Задачи и примеры этой главы помогут учащимся восстановить навыки в алгебраических и тригонометрических преобразованиях. Это дает возможность использовать книгу абитуриентам для подготовки к вступительным экзаменам в вузы. Имеется большое количество примеров и задач для самостоятельного решения. Ко всем задачам в конце книги даны ответы, а ко многим — указания и решения. В конце каждой главы даны вопросы для конспектирования. Кроме того, каждая глава содержит два варианта контрольных заданий, которые позволяют учащимся самостоятельно проверять усвоение программного материала по математике. Учебное пособие адресовано учащимся средних специальных учебных заведений.

Название: Stochastic Methods for Modeling and Predicting Complex Dynamical Systems: Uncertainty Quantification, State Estimation, and Reduced-Order Models
Автор: Nan Chen
Издательство: Springer
Серия: Synthesis Lectures on Mathematics & Statistics
Год: 2023
Страниц: 208
Язык: английский
Формат: pdf (true), epub
Размер: 27.2 MB

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. Machine Learning has become a prevalent and powerful tool to advance the modeling and forecast of many complex dynamical systems. One of the main advantages of machine learning is its computational efficiency. In fact, once a Machine Learning model is trained, the forecast utilizing such a model is often much cheaper than numerically integrating a traditional high-dimensional nonlinear dynamical model made up of explicit parametric terms.

Название: Fuzzy Systems Modeling in Environmental and Health Risk Assessment
Автор: Boris Faybishenko, Rehan Sadiq
Издательство: Wiley
Год: 2023
Страниц: 332
Язык: английский
Формат: pdf (true)
Размер: 15.8 MB

Fuzzy Systems Modeling in Environmental and Health Risk Assessment Demonstrates the successful application of fuzzy systems modeling to real-world environmental and health problems. In Fuzzy Systems Modeling in Environmental and Health Risk Assessment, a team of distinguished researchers delivers an up-to-date collection of the most successful and innovative attempts to apply fuzzy logic to problems involving environmental risk assessment, healthcare decision-making, the management of water distribution networks, and the optimization of water treatment and waste management systems. By explaining both the theoretical and practical aspects of using fuzzy systems modeling methods to solve complex problems, analyze risks and optimize system performance, this handy guide maintains a strongly application-oriented perspective throughout, offering readers a practical treatment of a cutting-edge subject. Since the pioneering work of Lotfi Zadeh, fuzzy logic (FL) analysis has been applied successfully in many scientific and real-life engineering situations, such as electrical, mechanical, civil, chemical, aerospace, agricultural, biomedical, computer, environmental, geological, industrial, etc.

Название: Recycling For Dummies
Автор: Sarah Winkler
Издательство: For Dummies
Год: 2023
Страниц: 403
Язык: английский
Формат: pdf (true)
Размер: 20.1 MB

Learn the facts about recycling and discover the best way to make an impact. Recycling is a simple action we can take that has an immediate positive effect. It keeps waste out of landfills, conserves natural resources, prevents pollution, and saves energy. Who wouldn’t want to do this? But recycling isn’t always straightforward. With so many different rules, it can be tough to work out the right thing to do. If you’re worried that you’re not recycling properly, or wondering whether you could be recycling more, this is the book for you. Recycling For Dummies cuts through the confusion around what you can and can’t recycle. This easy-to-follow manual breaks down recycling codes, symbols, and rules in a straightforward way that anyone can understand and apply.

Название: Эволюционные модели в дискретной оптимизации: монография
Автор: Козин И.В.
Издательство: Запорожье: Запорожский национальный университет
Год: 2019
Страниц: 204
Формат: djvu
Размер: 20,8 Мб
Язык: Русский


Одно из направлений математического моделирования, которое за основу поиска оптимальных решений берет принципы природной эволюции рассматривается в предлагаемой работе. В рамках этого направления развивается теория генетических алгоритмов, эволюционные вычисления, эволюционное программирование.

Название: Applied Categorical and Count Data Analysis, 2nd Edition
Автор: Wan Tang, Hua He, Xin M. Tu
Издательство: CRC Press
Год: 2023
Страниц: 395
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments. The second edition covers classic concepts and popular topics, such as contingency tables, logistic regression models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. As in the first edition, R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies.