Loss-Aware Histogram Binning and Principal Component Analysis for Customer Fleet Analytics
We propose a method to estimate information loss when conducting histogram binning and principal component analysis (PCA) sequentially, as usually done in practice for fleet analytics. Coarser-grained histogram binning results in less data volume, fewer dimensions, but more information loss. Conside...
Saved in:
Main Authors: | Kunxiong Ling, Jan Thiele, Thomas Setzer |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Open Journal of Intelligent Transportation Systems |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10437985/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Reducing the dynamic range of infrared images based on block-priority equalization and compression of histograms
by: S. I. Rudikov, et al.
Published: (2022-06-01) -
Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models
by: Yaoyao Ren, et al.
Published: (2024-12-01) -
Balancing efficiency and sustainability in waste collection fleet operations: A fleet optimization and electrification perspective in a real case study
by: M. Ghoreishi, et al.
Published: (2025-02-01) -
Merchant Fleet Performance of Türkiye: A CRITIC-based TOPSIS Approach
by: Maruf Gögebakan, et al.
Published: (2024-06-01) -
Recognition of Hand Gestures Using Image with Histogram Feature Extraction and Euclidean Distance Classification Method
by: Yenni Astuti, et al.
Published: (2024-12-01)