An Explainable q-Rung Orthopair Fuzzy Entropy-COPRAS Framework for Green Hydrogen Site Selection under Uncertainty
不確実性下のグリーン水素サイト選定のための説明可能なq-ラング直交対ファジィエントロピー-COPRASフレームワーク (AI 翻訳)
Dr.Navneet Kumar Assistant Professor, P.G. Department of Mathematics, Purnea University Purnia
🤖 gxceed AI 要約
日本語
本論文は、不確実性下でのグリーン水素サイト選定のための説明可能なq-ラング直交対ファジィエントロピー-COPRASフレームワークを提案する。再生可能エネルギー、水、グリッド、需要、土地利用、生態リスク、社会的受容性などの複数基準を考慮し、客観的加重とランキングを行う。5つの候補地のベンチマーク評価の結果、産業港湾ブラウンフィールドが最適とされた。
English
This paper proposes an explainable q-rung orthopair fuzzy Entropy-COPRAS framework for green hydrogen site selection under uncertainty. It integrates multiple criteria including renewable energy, water, grid, demand, land use, ecological risk, and social acceptance to derive objective weights and rank sites. Benchmarking five candidate sites shows that an industrial port brownfield achieves the highest utility score, followed by a coastal renewable hub. The framework supports transparent and interpretable hydrogen infrastructure planning.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本はグリーン水素の大規模導入を目指しており、サイト選定は重要な課題である。本フレームワークは、複数基準と不確実性を扱う実用的な意思決定ツールとして、日本の水素ハブ計画やGX投資判断に活用できる。
In the global GX context
Green hydrogen is a key pillar of global decarbonization. This framework provides a transparent, interpretable method for site selection that can inform investment and policy decisions in countries developing hydrogen infrastructure. Its sensitivity analysis enhances credibility and supports stakeholder engagement.
👥 読者別の含意
🔬研究者:Useful for those working on decision-making under uncertainty for hydrogen infrastructure planning, providing a transparent multi-criteria framework with sensitivity analysis.
🏢実務担当者:Site selection teams and hydrogen project developers can apply this framework to evaluate candidate sites systematically, balancing multiple conflicting criteria.
🏛政策担当者:Regulators and energy planners can use the framework to assess and prioritize hydrogen hub locations, integrating environmental and social factors with technical and economic criteria.
📄 Abstract(原文)
Green hydrogen site selection is a complex multi-criteria decision-making problem involving renewable-energy availability, water access, grid connectivity, industrial demand, land-use constraints, ecological risk, and social-permitting feasibility. Because these criteria are conflicting, heterogeneous, and often judged under uncertainty, this study proposes an explainable q-rung orthopair fuzzy Entropy-COPRAS framework for robust site evaluation. q-rung orthopair fuzzy sets are employed to represent positive, negative, and hesitant expert assessments within a flexible mathematical structure suitable for generalized uncertainty modelling. An entropy-based weighting procedure is developed to derive objective criterion weights from the dispersion of q-rung orthopair fuzzy score information, reflecting information-theoretic uncertainty. The COPRAS method is extended to rank candidate sites by separately considering benefit-type and cost-type criteria according to the complex proportional assessment principle. To improve transparency, the framework incorporates sensitivity analysis through q-parameter variation, weight perturbation, criterion ablation, and criterion-level contribution diagnosis. A reproducible benchmark with five candidate green hydrogen sites and seven criteria demonstrates the approach. Results show that the industrial port brownfield achieves the highest utility score, followed by the coastal renewable hub and inland solar belt. The framework supports transparent, interpretable, and sustainable hydrogen infrastructure planning under uncertain decision environments for planners, investors, regulators, and energy-system decision makers globally.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/21444528first seen 2026-07-20 04:13:09
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