GeoClimate-FusionLLM: Explainable Multi-Modal Environmental Early-Warning Pipeline
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2026
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| _version_ | 1866901686234120192 |
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| author | Ahmed, Shaheen Mohammed Saleh Ahmed, Shaheen Mohammed Saleh |
| author_facet | Ahmed, Shaheen Mohammed Saleh Ahmed, Shaheen Mohammed Saleh |
| contents | <p>Corrected citation metadata and released the reproducible GeoClimate-FusionLLM environmental early-warning repository for Zenodo archiving and DOI generation.</p> <p>This release includes Python code, Baghdad 2019–2024 climate data workflow, leakage-safe preprocessing, multimodal feature engineering, classical forecasting baselines, deep-learning models, ablation experiments, parameter-count analysis, three-random-seed robustness testing, extreme-temperature evaluation, explainability outputs, and environmental early-warning report generation.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20237609 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | GeoClimate-FusionLLM: Explainable Multi-Modal Environmental Early-Warning Pipeline Ahmed, Shaheen Mohammed Saleh Ahmed, Shaheen Mohammed Saleh climate forecasting environmental early warning deep learning explainable AI multimodal data fusion <p>Corrected citation metadata and released the reproducible GeoClimate-FusionLLM environmental early-warning repository for Zenodo archiving and DOI generation.</p> <p>This release includes Python code, Baghdad 2019–2024 climate data workflow, leakage-safe preprocessing, multimodal feature engineering, classical forecasting baselines, deep-learning models, ablation experiments, parameter-count analysis, three-random-seed robustness testing, extreme-temperature evaluation, explainability outputs, and environmental early-warning report generation.</p> |
| title | GeoClimate-FusionLLM: Explainable Multi-Modal Environmental Early-Warning Pipeline |
| topic | climate forecasting environmental early warning deep learning explainable AI multimodal data fusion |
| url | https://doi.org/10.5281/zenodo.20237609 |