Occupational Health and Safety Risk Assessment of Cruise Ship Construction Based on Improved Intuitionistic Fuzzy TOPSIS Decision Model

Table 1

Comparison of risk assessment methods.

Method	Features
LEC evaluation method	Practical and straightforward but lacking flexibility and subjective
Analytic network process (ANP)	Reflects the dependence between the hierarchical structure but needs to study the relationship between the factors; the workload is relatively large.
TOPSIS method	Simple calculation, full use of original data, and less information loss, but strong subjectivity
FMEA method	Effectively determines failure modes and failure causes and predicts the types of failures that may occur; however, the connection between the various units of the system is not considered.
Monte Carlo method (MCM)	The algorithm is simple, and the process is flexible; however, the amount of data is large, and the data requirements are strict.
Artificial neural network (ANN) method	Has strong self-learning ability and avoids artificial setting of weights, but takes longer time.
Analytic hierarchy process (AHP)	Comprehensive consideration of qualitative and quantitative. However, when there are too many indicators, the data statistics are large. The weight of the indicators is difficult to determine.
Fuzzy comprehensive evaluation (FCE) method	According to the membership degree theory of fuzzy mathematics, the qualitative evaluation is transformed into a quantitative evaluation method. The result is clear and systematic, suitable for solving nondeterministic problems, but the calculation is complex and subjective.