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

Publication2025

Forest Fire Forecasting Model in Wildlife Using Reinforcement Learning Agent for Reward Maximization

The record

Type
Publication
Date
1 January 2025
Level
National
Journal
Lecture Notes in Networks and Systems
Volume
1396 LNNS
Pages
51-60
Published
1 January 2025
DOI
10.1007/978-981-96-6124-4_5
Scopus ID
105018905731
ISSN
23673370
Authors
6
Open access
No
Citations
0
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 13 Take urgent action to combat climate change and its impacts

    GoalPrimaryHigh confidenceJudged

    Forest fire forecasting using reinforcement learning for climate-resilient disaster risk reduction.

    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
  2. 15 Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss

    GoalSecondaryHigh confidenceJudged

    Ecosystem protection through predictive wildfire models for biodiversity conservation.

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

Viksit Bharat @2047

  1. vb-2.5 Green economy, energy transition and climate resilience

    Sub-themePrimaryHigh confidenceJudged

    Climate resilience and environmental protection through AI-powered forest fire prediction systems.

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

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KIIT Deemed to be University. “Forest Fire Forecasting Model in Wildlife Using Reinforcement Learning Agent for Reward Maximization”. Kortex.

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