Shulph Ink
Engineering Analytics: Advances in Research and Applications
Engineering Analytics: Advances in Research and Applications
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- More about Engineering Analytics: Advances in Research and Applications
Engineering analytics is becoming a necessary skill for engineers, and this book provides an introduction to it. It covers basic methods in visual, descriptive, predictive, and prescriptive analytics and Big Data, with industrial case studies and example problem demonstrations. It is intended for professionals wanting to work on analytical problems, Engineering students, Researchers, Chief-Technology Officers, and Directors.
Format: Hardback
Length: 268 pages
Publication date: 27 September 2021
Publisher: Taylor & Francis Ltd
Engineering analytics is fast emerging as a crucial skill for engineers across various domains. By harnessing the power of massive data, areas such as Operations Research, Simulation, and Machine Learning undergo profound transformations. This comprehensive book serves as an introductory guide to engineering analytics, aimed at enhancing performance tracking, customer segmentation for resource optimization, patterns and classification strategies, and logistics control towers.
Within its pages, fundamental methods in visual, descriptive, predictive, and prescriptive analytics, as well as Big Data, are introduced. Industrial case studies and example problem demonstrations seamlessly reinforce the concepts and applications, making the material engaging and practical.
The book then delves into visual analytics, exploring its relationships with other domains. It also provides comprehensive coverage of simulation, considering its dimensions and perspectives from different paradigms, including Machine Learning and Artificial Intelligence.
Designed specifically for professionals seeking to solve analytical problems, engineering students, researchers, Chief-Technology Officers, and Directors working in the fields of Industrial Engineering, Computer Science, Statistics, Electrical Engineering Operations Research, and Big Data will find this book invaluable. It serves as a comprehensive resource for advancing their understanding and expertise in engineering analytics.
Weight: 560g
Dimension: 159 x 242 x 24 (mm)
ISBN-13: 9780367685348
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