Evaluation for the Safety Ability of Tower Control Instructor Based on Discrete Hopfield Neural Network

Aiming at the problem that the safety ability of tower control instructors cannot be quantitatively evaluated, based on the working characteristics of tower control instructors, this paper puts forward the definition of safety capability of tower control instructors, combined with expert experience and actual operating conditions, established a tower control instructor with 11 indicators Index system of safety capability evaluation. Analyze the feasibility of applying discrete Hopfield neural network to the safety ability assessment of tower control instructors, and convert the discrete Hopfield neural network into MATLAB operation program. 20 representative tower control instructors were selected as the data source for designing ideal level assessment indicators, and the safety capability data of 5 tower control instructors to be evaluated were introduced and their safety capability levels were quantitatively evaluated. The results showed that the discrete Hopfield neural network can easily realize the quantitative evaluate of the safety ability of the tower control instructors.