*4.4. Discussion*

According to above two numerical examples, we can easily find our proposed methods can express more fuzzy information and apply broadly situations in real MADM problems. Based on the q-rung orthopair fuzzy set (q-ROFS), we developed ten q-rung orthopair fuzzy similarity measures; our research results are more suitable for MADM problems than intuitionistic fuzzy similarity measures and Pythagorean fuzzy similarity measures. For pattern recognition problems, we accurately allocated the unknown building material *A* to the known building material *A*2. For scheme selection, by utilizing our developed ten similarity measures, we obtained the best scheme selection of construction project.

Furthermore, in complicated decision-making environment, the decision-maker's risk attitude is an important factor to think about, our methods can make this come true by altering the parameters whereas other decision-making ways such as q-ROFWA and q-ROFWA operator do not have the ability that dynamic adjust to the parameter according to the decision maker's risk attitude, so it is di fficult to solve the risk multiple attribute decision-making in real practice.
