Publication2011
Lateral displacement of liquefaction induced ground using least square support vector machine
- Industry, Innovation and Infrastructure
- Sustainable Cities and Communities
- Partnerships for the Goals
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 July 2011
- Level
- International — held abroad
- Journal
- International Journal of Geotechnical Earthquake Engineering
- Volume
- 2
- Issue
- 2
- Pages
- 29-39
- Published
- 1 July 2011
- DOI
- 10.4018/jgee.2011070103
- Scopus ID
- 84864531313
- ISSN
- 19478488
- Authors
- 5
- Open access
- No
- Citations
- 2
- International co-authorship
- Yes
- Co-author countries
- AU, IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
11 Make cities and human settlements inclusive, safe, resilient and sustainable
Least square support vector machine predicts lateral ground displacement during earthquake-induced liquefaction, outperforming neural network models for disaster risk assessment.
- 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
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Infrastructure resilience technology for earthquake hazard prediction and mitigation.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- 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.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 11 label. Least square support vector machine predicts lateral ground displacement during earthquake-induced liquefaction, outperforming neural network models for disaster risk assessment.
- 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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Provenance
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- 1
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Citing this record
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KIIT Deemed to be University. “Lateral displacement of liquefaction induced ground using least square support vector machine”. Kortex.