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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2022

A Comparative Technique to detect and classify Power Quality Disturbances with Noise Signals

The record

Type
Publication
Date
1 January 2022
Level
National
Journal
2022 IEEE 3rd Global Conference for Advancement in Technology Gcat 2022
Published
1 January 2022
DOI
10.1109/gcat55367.2022.9972131
Scopus ID
85145435403
Authors
6
Open access
No
Citations
6
International co-authorship
No
Co-author countries
IN

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UN Sustainable Development Goals

  1. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetPrimaryModerate confidenceJudged

    Discrete wavelet transform and supervised machine learning classification algorithms for automatic detection and categorization of power quality disturbances in electrical distribution networks.

    Moderate confidence
    The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-3 Innovation, Science and Technology

    ThemePrimaryModerate confidenceJudged

    Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Discrete wavelet transform and supervised machine learning classification algorithms for automatic detection and categorization of power quality disturbances in electrical distribution networks.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “A Comparative Technique to detect and classify Power Quality Disturbances with Noise Signals”. Kortex.

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