Описание: This volume provides a brief review of the previous work on model reduction and identification of DPS, and develops new spatio-temporal models and their relevant identification approaches. All modeling approaches are applied to industrial thermal processes.
Автор: Gabriele Puppis Название: Automata for Branching and Layered Temporal Structures ISBN: 3642118801 ISBN-13(EAN): 9783642118807 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Since 2002, FoLLI awards an annual prize for an outstanding dissertation in the fields of Logic, Language, and Information. This book focuses on Logic and Computation and, more specifically, on automata-based decidability techniques for time granularity and on a fresh method for deciding Monadic Second Order theories of trees.
Автор: Yang Yun Название: Temporal Data Mining via Unsupervised Ensemble Learning ISBN: 0128116544 ISBN-13(EAN): 9780128116548 Издательство: Elsevier Science Рейтинг: Цена: 7241.00 р. Наличие на складе: Поставка под заказ.
Описание: Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. . Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. . Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.
Автор: Douzal-Chouakria Название: Advanced Analysis and Learning on Temporal Data ISBN: 3319444115 ISBN-13(EAN): 9783319444116 Издательство: Springer Рейтинг: Цена: 5870.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.
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