- 216 pages
- English
- PDF
- Available on iOS & Android
About this book
Classification of time series is an important task in various fields, e.g., medicine, finance, and industrial applications. This workdiscusses strong temporal classification using machine learningtechniques. Here, two problems must be solved: the detection ofthose time instances when the class labels change and the correctassignment of the labels. For this purpose the scenario-basedrandom forest algorithm and a segment and label approach areintroduced. The latter is realized with either the augmenteddynamic time warping similarity measure or with interpretablegeneralized radial basis function classifiers.The main application presented in this work is the detectionand categorization of car crashes using machine learning.Depending on the crash severity different safety systems, e.g., belt tensioners or airbags must be deployed at time instanceswhen the best-possible protection of passengers is assured.
Frequently asked questions
- Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
- Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.