Combination Weighting Method of Engineering Disciplines Evaluation Index Based on Soft Computing

The development of engineering disciplines is aided by research into constructing a characteristic index system, particularly when the blockchain technology is used. The key issue is how to choose multi-level evaluation indicators reasonably while also scientifically defining the weights of indicators at all levels. Subjective empowerment methods are insufficient in terms of subjective influence, whereas objective empowerment methods necessitate a large sample size, a practical problem domain, and complex calculation methods. In response to the need for characteristic index system construction and evaluation research, this paper identifies four first-level indicators, eleven second-level indicators, and twenty-one third-level indicators as the main evaluation dimensions including academic achievements, discipline strength, talent training, and international development. The proposed method combines the Fuzzy Analytic Hierarchy Process (AHP), based on triangular fuzzy numbers, with the critic weighting analysis method. It is establishing a multi-level evaluation index system to propose targeted combination weighting methods for the engineering disciplines. To avoid evaluation bias caused by the single use of subjective or objective weighting methods, the difference coefficient method is used for combined weighting based on subjective and objective information to calculate the weighting results. The experimental and modelling data show that the calculation and evaluation results of the algorithm proposed in this paper are promising and applicable in multiple domains where there is a hierarchy in the problem domain and multiple parameters participate in decision making. With the evaluation results of the proposed approach, the subjective weight obtained is 0.047, and the objective weight obtained is 0.253.