Improvement of CRADIS Natural Gas Pipeline Risk Evaluation Based on the Complex Spherical Fuzzy Numbers and Choquet Points Method

Risk assessment plays a crucial role in the supervision process of natural gas pipeline risks. The Fine-Kinney model is recognized as an effective risk assessment technique; however, there still exists a certain degree of deviation in the precision of risk analysis when addressing issues in a complex spherical fuzzy environment. This study focuses on the limitations present in the risk analysis of natural gas pipelines, particularly concerning ambiguous assessments and inadequate integration of weight factors. This paper presents an advanced Fine-Kinney framework that employs the distance to ideal solution (CRADIS) method, which incorporates complex spherical fuzzy numbers and utilizes the Choquet integral approach for risk assessment modeling. This model capitalizes on the precision of complex spherical fuzzy numbers and the CRADIS method, along with the comprehensiveness of the index relationship evaluation characteristic of the Choquet integral, thereby significantly improving the reliability and precision of the risk assessment process. To begin, an assessment index system for evaluating failure risks was developed using an enhanced Fine-Kinney methodology, grounded in the risk structure of natural gas pipelines. The priority coupled with the arithmetic average (AA) of complex spherical fuzzy numbers was integrated into the process of generating the group risk assessment matrix, ensuring that the priorities set by experts play a vital role in forming a precise and robust risk assessment framework. During the data processing phase aimed at refining CRADIS, a comparison matrix was created, and the weights of the risk evaluation indicators were established using the Choquet integral, which thereby highlights the impact of interconnected risk factors and enhances the model’s capacity to address uncertainty. Ultimately, the ranking of occupational hazards was established by analyzing instance data related to natural gas pipelines. Through a comparison of various models, the sensitivity of the calculation parameters was examined, which in turn validated the stability and reliability of the enhanced CRADIS risk assessment model. Experimental findings suggest that this model improves the objectivity of data weighting, decreases fuzzy factors present in the data, and allows for an accurate assessment of risk priorities, thus offering valuable theoretical backing for the evaluation of natural gas pipelines.