Data decision based promoting effect of non-destructive detection skill competition on detection technology course teaching in colleges and universities

Abstract

The construction of a non-destructive testing skills competition system is based on data decision technology in this paper. The distribution of each data pheromone is initialized using the Euclidean distance algorithm, and the probability value of each parameter is calculated using weighting coefficients. Then, the decision tree algorithm is used to sort the gain nodes of each information feature value, and accurate data classification is achieved by continuously updating the information entropy value. According to the final results, the students’ passing rate in the competition is about 79.8% on average, and their cognitive rate has increased by about 54.3% on average. The NDT skills competition system has helped improve the teaching quality of testing technology in colleges and universities.

Keywords

• data decision making
• nondestructive testing
• euclidean distance
• skills competition
• information entropy value
• 97p12