Publication2024
Distributed machine learning strategies for efficient development of direct and inverse nonlinear and IIR models
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Journal of Ambient Intelligence and Humanized Computing
- Volume
- 15
- Issue
- 1
- Pages
- 1103-1114
- Published
- 1 January 2024
- DOI
- 10.1007/s12652-018-0839-7
- Scopus ID
- 85049591455
- ISSN
- 18685137
- Authors
- 3
- Open access
- No
- Citations
- 1
- International co-authorship
- No
- Co-author countries
- IN
Classification
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UN Sustainable Development Goals
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Applies distributed machine learning strategies including particle swarm optimization and differential evolution for parameter estimation of nonlinear IIR systems.
- 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
vb-3.2 Digital technology and artificial intelligence
Distributed machine learning algorithms and bio-inspired optimization represent computational intelligence and digital technology advancement.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Distributed machine learning strategies for efficient development of direct and inverse nonlinear and IIR models”. Kortex.