关键词: 效能评估, MLP, 海上无人跨域协同系统, ADC模型, 层次分析法

Abstract:

In the face of the problem of evaluating the detection capability effectiveness of the maritime unmanned cross-domain collaborative system, it is necessary to study the evaluation indexes and evaluation algorithm. In this paper, the robot's own parameters and environmental parameters are combined to build a calculation model for evaluation indexes, such as detection coverage rate, repeated detection rate, the number of pixels per unit area, and energy as well as an evaluation system for detection capability of the maritime unmanned cross-domain collaborative system. The subjectivity in the evaluation process is reduced, and training data is generated by the availability dependability capability (ADC) method combined with analytic hierarchy process. The multilayer perceptron (MLP) neural network method was used to objectively measure the effectiveness of the system. The results showed that the size of the generated data set reached 20,000, and the evaluation error of the model was less than 3%, which verified its effectiveness and applicability. Meanwhile, the PyQt5 framework was used to build the evaluation system interface, realizing the functions of environment modeling, data entry, and effectiveness evaluation.

Key words: effectiveness evaluation, multilayer perceptron(MLP), maritime unmanned cross-domain collaborative system, ADC model, analytic hierarchy process