Work

CMDA: a tool for Continuous Monitoring Data Analysis

Year: 2023

Type: preprint

Abstract: Over the last few years, with the growth of time-series collecting and storing, there has been a great demand for tools and software for temporal data engineering and modeling. This paper presents a generic workflow for time series data research, including temporal data importing, preprocessing, and feature extraction. This framework is developed and built as a robust and easy-to-use Python package, called CMDA, with a modular structure that offers tools to prepare raw data, allowing both scientists and non-experts to analyze various temporal data structures.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2310.14427

Authors: Ghalati, Pejman Farhadi, Schuppert, Andreas

Institution: RWTH Aachen University

Language: English

Topic: Time Series Analysis and Forecasting

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4387929170

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