A BO-CNN-Based System Interoperability Assessment Model
Shouda Jiang, Qian Zhou, Yunlong Sheng, Zhiying Zhang, Changan Wei, Ji Xu · 2024
In today's era of joint operations, interoperability has become an advantage to win on the battlefield. Evaluating the interoperability of a system accurately is a significant issue. A novel assessment model is proposed, which utilizes convolutional neural networks and builds upon the analysis of prevalent interoperability assessment models. Convolutional neural networks are used for extracting interoperability features, and Bayesian optimization is used for optimizing the parameters of convolutional neural networks. The experimental findings provide evidence that the model presented in this paper offers practical significance for assessing interoperability.