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

Publication2025

An Attention-enabled Spatiotemporal Deep Hybrid Model for Cloud Load Forecasting

The record

Type
Publication
Date
1 January 2025
Level
National
Journal
Proceedings 2025 IEEE 3rd International Symposium on Sustainable Energy Signal Processing and Cybersecurity Isssc 2025
Published
1 January 2025
DOI
10.1109/isssc66652.2025.11388455
Scopus ID
105035006051
Authors
4
Open access
No
Citations
0
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 9.c Significantly increase access to ICT and provide universal and affordable access to the internet

    TargetPrimaryHigh confidenceJudged

    Deep learning model for cloud workload prediction enables efficient resource allocation and infrastructure optimization in cloud data centers.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    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-3.2 Digital technology and artificial intelligence

    Sub-themePrimaryHigh confidenceJudged

    Machine learning for infrastructure optimization demonstrates digital technology and AI capability development.

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

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KIIT Deemed to be University. “An Attention-enabled Spatiotemporal Deep Hybrid Model for Cloud Load Forecasting”. Kortex.

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