Название: Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2022-Winter
Автор: Roger Lee
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 165
Язык: английский
Формат: pdf (true), epub
Размер: 26.3 MB

This edited book presents scientific results of the 24th ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2022-Summer) which was held on December 7–9, 2022, at Taichung, Taiwan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. The conference organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 15 of the most promising papers are then published in this Springer (SCI) book and not the conference proceedings. Reinforcement Learning (RL) is a powerful tool and has been increasingly used in continuous control tasks such as locomotion and balancing in robotics.

Название: Concurrency, Specification and Programming: Revised Selected Papers from the 29th International Workshop on Concurrency
Автор: Bernd-Holger Schlingloff, Thomas Vogel, Andrzej Skowron
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 234
Язык: английский
Формат: pdf (true), epub
Размер: 21.9 MB

This book presents novel approaches to the formal specification of concurrent and parallel systems, mathematical models for describing such systems, and programming and verification concepts for their implementation. A special emphasis is on methods based on artificial intelligence and machine learning techniques. Chapters are revised selected papers from the 29th International Workshop on Concurrency, Specification, and Programming (CS&P 2021), Berlin, Germany. Nine independent chapters cover formal approaches to topics such as requirements formalization, parsing, or granular computing, as well as their applications in recommender systems, decision making, security, optimization, and other areas. The book thus addresses both researchers and practitioners in its field.

Название: Python для хакеров. Нетривиальные задачи и проекты
Автор: Воган Ли
Издательство: Питер
Год: 2023
Формат: pdf
Страниц: 384
Размер: 28,8 Мб
Язык: русский

«Python для хакеров. Нетривиальные проекты и задачи» делает упор на реальные проекты, так что от экспериментирования с синтаксисом вы сразу перейдете к написанию полноценных программ. Развивая свои навыки разработки на Python, вы будете проводить научные опыты, изучать статистику и решать задачи, которые не давали покоя гениям на протяжении многих лет, и даже займетесь обнаружением далеких экзопланет. Каждая глава начинается с четко поставленной цели и обсуждения способов решения задачи. Далее следует собственно миссия и стратегия действий, построенная таким образом, чтобы вы научились мыслить как программист. Вы будете руководить спасательной операцией береговой охраны, спланируете и осуществите полет космического корабля на Луну, реализуете ограничение доступа в секретную лабораторию с помощью распознавания лиц и не только это. Программы, представленные в книге, не отпугнут даже новичков. Вы будете осваивать все более сложные техники и наращивать навыки написания кода. Справившись со всеми миссиями, вы будете готовы к самостоятельному решению любых сложных реальных задач с помощью Python.

Название: Теория и проектирование быстрых перестраиваемых преобразований и слабосвязанных нейронных сетей
Автор: Дорогов А.Ю.
Издательство: СПб.: Пoлитехника
Год: 2014
Формат: pdf
Страниц: 327
Размер: 19 mb
Язык: Русский

В монографии дается современное изложение теории проектирования алгоритмов быстрых преобразований и модульных нейронных сетей. С системных позиций рассматриваются быстрые преобразования и многослойные нейронные сети с прореженным набором связей и модульной организацией. Предложены алгоритмы структурного проектирования и обучения перестраиваемых быстрых преобразований и нейронных сетей.

Название: Computational Intelligence Aided Systems for Healthcare Domain
Автор: Akshansh Gupta, Hanuman Verma, Mukesh Prasad
Издательство: CRC Press
Год: 2023
Страниц: 437
Язык: английский
Формат: pdf (true)
Размер: 79.4 MB

This book covers recent advances in Artificial Intelligence (AI), smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. Machine Learning is a learning process by the computing device; that is the study of computer algorithms that improve automatically through experience and by using input data. Thus, the machine learning algorithms are processes that can learn from the data. This is accomplished with the minimum extent of human intervention without explicit programming like in abstraction form. The learning process in Machine Learning is improved based on the experiences of the machines throughout the execution process. It builds a model or map based on training data that can be used to make predictions or decisions.

Название: Introductory Applied Statistics: With Resampling Methods & R
Автор: Bruce Blaine
Издательство: Springer
Год: 2023
Страниц: 197
Язык: английский
Формат: pdf (true), epub
Размер: 27.8 MB

Includes data analytic examples in R. This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text teaches statistical inference principles using resampling methods (such as randomization and bootstrapping), covering methods for hypothesis testing and parameter estimation. These methods are applied to each statistical model introduced in preceding chapters. Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions required for basic data analysis in each of the four models. The text also includes introductory guidance to the fundamentals of data wrangling, as well as examples of write-ups so that students can learn how to communicate findings. Each chapter includes problems for practice or assessment. Supplemental instructional videos are also available as an additional aid to instructors, or as a general resource to students.

Название: Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges
Автор: Ziheng Sun, Nicoleta Cristea, Pablo Rivas
Издательство: Elsevier
Год: 2023
Страниц: 430
Язык: английский
Формат: pdf (true)
Размер: 42.9 MB

Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. Artificial Intelligence (AI) technologies have been aggressively experimented with in Earth system sciences and attempted to solve these urgent problems and provide a solution for those ultimate challenges of humanity. Deep Learning has become one of the most popular research areas and could almost be seen in every branch of Earth sciences today. The idea behind Deep Learning is based on adding more hidden layers to the neural network, using a series of methods to control the model regularization and balance between overfitting and underfitting.

Название: Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods
Автор: Kemal Polat, Saban Ozturk
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 303
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Deep learning (DL), which has transformed several industries over the past ten years, has astounded practitioners with its amazing performance across nearly all application domains. The following fundamental ideas related to DL can be arranged in order of breadth to depth: (1) the brain-inspired artificial neural network (ANN) algorithm; (2) Machine Learning (ML) methods that allow machines to learn from examples without having to be explicitly programmed; and (3) Artificial Intelligence (AI), a theory that aims to artificially mimic the intelligent behavior of beings found in nature.

Автор: Е. С. Кузин, А. И. Ройтман, И. Б. Фоминых, Г. К. Хахалин. Ред. Ю. М. Смирнов
Название: Интеллектуализация ЭВМ. Перспективы развития вычислительной техники, выпуск 2
Издательство: М:, Высшая школа
Год: 1989
Страниц: 159
Формат: DJVU, PDF
Размер: 12 МБ
В пособии рассматриваются основные направления создания средств интеллектуализации ЭВМ, характерные для вычислительных машин пятого поколения. Описываются средства представления и хранения знаний в ЭВМ, средства автоматического и автоматизированного решения задач, средства общения пользователя и вычислительной системы, обеспечивающие естественные для человека способы представления сообщений, экспертные системы.

Название: Deep Learning in Time Series Analysis
Автор: Arash Gharehbaghi
Издательство: CRC Press
Год: 2023
Страниц: 208
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Deep Learning is an important element of Artificial Intelligence, especially in applications such as image classification in which various architectures of neural network, e.g., convolutional neural networks, have yielded reliable results. This book introduces Deep Learning for time series analysis, particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of Machine Learning, including students, engineers, researchers, and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the Deep Learning methods for time series analysis.