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-Rung Orthopair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
グリーン水素サイト選定は、再生可能エネルギー、水、送電網、土地利用、生態リスク、社会的受容性といった複数の基準を評価する複雑な意思決定問題である。本研究では、q-rung orthopairファジィ集合を用いたエントロピーCOPRASフレームワークを提案し、不確実性下でのサイト評価と順位付けを可能にする。産業ポートのブラウンフィールドが最も高い効用スコアを示し、説明可能な感度分析により透明性を確保した。
English
This study proposes an explainable q-rung orthopair fuzzy Entropy-COPRAS framework for green hydrogen site selection under uncertainty. It considers renewable energy availability, water access, grid connectivity, and social feasibility. A benchmark with five sites shows that an industrial port brownfield achieves the highest utility score. 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
日本では、政府がグリーン水素の導入目標を掲げ、港湾や再生可能エネルギー適地での水素ハブ構築が進む。本フレームワークは、SSBJやESG開示が求める立地選定の透明性・説明可能性に直接貢献し、国内の水素サプライチェーン設計に実践的示唆を与える。
In the global GX context
Global hydrogen deployment requires transparent site selection under uncertain conditions. This framework aligns with ISSB and TCFD expectations for climate infrastructure planning, offering a reproducible method for evaluating green hydrogen sites. It strengthens the decision-making process for investors and regulators in the hydrogen transition.
👥 読者別の含意
🔬研究者:Useful for MCDM researchers and hydrogen infrastructure analysts in applying fuzzy sets under uncertainty.
🏢実務担当者:Corporate planners and investors can use this framework to evaluate hydrogen project locations with transparent criteria.
🏛政策担当者:Regulators can adopt the methodology for designing hydrogen hub policies and site selection guidelines.
📄 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/21361996first seen 2026-07-15 04:25:37
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