Advanced Risk Analysis of Submarine Pipelines Through Ewbp-Weighted It2 Fuzzy Cetopsis Evaluation System

Abstract

Submarine pipelines are vital for oil/gas transportation, requiring robust risk assessment for intelligent monitoring. To address chaotic risk levels, ambiguous indicator weights, and inadequate prevention measures, this study proposes a novel FMEA-based model integrating: (1) An entropy weight-bidirectional projection (EWBP) method for objective indicator weighting, combining information entropy and data compromise theory to avoid bias; (2) An interval type-2 fuzzy cross-entropy TOPSIS (IT2-FCETOPSIS) algorithm, converting weighted IT2 fuzzy data into interval-valued intuitionistic fuzzy matrices to preserve evaluation accuracy while enhancing discrimination via cross-entropy. Validated with real pipeline data, the model outperforms alternatives in risk prioritization and sensitivity to relaxation factors, offering theoretical support for intelligent pipeline risk management.

Keywords: Entropy weight-bidirectional projection projection (EWBP) empowerment method, Interval type-2 fuzzy cross entropy-TOPSIS (IT2-FCETOPSIS) method, Multi-attribute risk evaluation, Submarine pipelines, Failure modes and effects analysis (FMEA)