This chapter deals with the development and optimization of algorithms for unsupervised pattern discovery in time series. While this work focuses on automotive time series data, the proposed approach, in general, is able to improve the handling of highly dynamic sensor data independently of its origin.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Development of Pattern Discovery Algorithms for Automotive Time Series


    Additional title:

    AutoUni – Schriftenreihe


    Contributors:


    Publication date :

    2022-03-24


    Size :

    30 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Unsupervised pattern discovery in automotive time series : pattern-based construction of representative driving cycles

    Noering, Fabian Kai Dietrich / Technische Universität Braunschweig / Springer Fachmedien Wiesbaden | TIBKAT | 2022


    Automotive pattern drafting

    Scholl, Warren | Engineering Index Backfile | 1923


    Method for time series structure discovery

    YAMADA KENJI / BHATTACHARYYA RAJAN / JAMMALAMADAKA ARUNA et al. | European Patent Office | 2023

    Free access

    Method for time series structure discovery

    YAMADA KENJI / BHATTACHARYYA RAJAN / JAMMALAMADAKA ARUNA et al. | European Patent Office | 2021

    Free access