Автор: Fox, William P ; Burks, Robert E Название: Modelling Operations Research and Business Analytics ISBN: 1032717556 ISBN-13(EAN): 9781032717555 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Fox, William P ; Burks, Robert E Название: Modelling Operations Research and Business Analytics ISBN: 1032735929 ISBN-13(EAN): 9781032735924 Издательство: Taylor&Francis Рейтинг: Цена: 48990.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Paczkowski, Walter R. Название: Deep Data Analytics for New Product Development ISBN: 0367077752 ISBN-13(EAN): 9780367077754 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Невозможна поставка. Описание: This book presents and develops the deep data analytics for providing the information needed for successful new product development.
Автор: Samanta Debabrata, Islam Sk Hafizul, Chilamkurti Naveen Название: Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications ISBN: 0367715112 ISBN-13(EAN): 9780367715113 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements.
Автор: Edited By P.N. Belkhode, J.P. Modak, V. Vidyasagar Название: Mathematical modelling and simulation : ISBN: 0367676354 ISBN-13(EAN): 9780367676353 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explains the concept of man-machine systems by using the mining industry. The goal is to use a mathematical model based approach to improve the quality of human life of the workers and operators with the enhancement of productivity by controlling the process variables.
Автор: Sujatha R., Aarthy S. L., Vettriselvan R. Название: Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics ISBN: 0367466635 ISBN-13(EAN): 9780367466633 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems.
Автор: Cachon, Gerard Terwiesch, Christian Название: Operations management ISBN: 1260547612 ISBN-13(EAN): 9781260547610 Издательство: McGraw-Hill Рейтинг: Цена: 65190.00 T Наличие на складе: Поставка под заказ. Описание: Cachon Operations Management 2e is designed for undergraduate students taking an introductory course in Operations Management. This text will share many of the strengths of Matching Supply with Demand: An Introduction to Operations Management. Operations Management by Cachon comprehensively spans the relevant domain of topics, is accessible to a typical undergraduate student (i.e., limited real world business experience), incorporates the latest research and knowledge, and provides thorough pedagogical support for instructors along with innovative learning support for students.
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Автор: Kessels Название: Traffic Flow Modelling ISBN: 3319786946 ISBN-13(EAN): 9783319786940 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces readers to the main traffic flow modelling approaches and discusses their features and applications.
Автор: Hammer Название: Management Approach for Resource-Productive Operations ISBN: 3658229381 ISBN-13(EAN): 9783658229382 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Markus Hammer investigates a time-based and analytics-supported operations management approach. He explores five perspectives: 1) the needs of industry, in particular manufacturing in process industries, 2) the impact of digitization, with focus on Big Data and analytics, 3) the management of operations through time-based performance metrics, 4) how operations improvement methods and advanced process control help achieve resource-productive operations and 5) learning from practice based on two empirical case studies. The author conceives, explains, and tests an implementation methodology. The final case study proves that the developed implementation methodology works in practice.
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