Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Compression of an Array of Similar Crash Test Simulation Results

Compression of an Array of Similar Crash Test Simulation Results

Muller, Stefan Peter

Paperback

General ComputersGeneral Construction & RenovationGeneral Mathematics

Currently unavailable to order

ISBN10: 3832554440
ISBN13: 9783832554446
Publisher: Logos Verlag Berlin
Published: Feb 5 2022
Pages: 232
Weight: 0.90
Height: 0.56 Width: 6.70 Depth: 9.38
Language: English
Big data thrives on extracting knowledge from a large number of data sets. But how is an application possible when a single data set is several gigabytes in size? The innovative data compression techniques from the field of machine learning and modeling using Bayesian networks, which have been theoretically developed and practically implemented here, can reduce these huge amounts of data to a manageable size. By eliminating redundancies in location, time, and between simulation results, data reductions to less than 1 % of the original size are possible. The developed method represents a promising approach whose use goes far beyond the application example of crash test simulations chosen here.

Also in

General Computers

View All